NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "mysql_identifier_quote_character" /apps/nobleprog-website/includes/functions/new-modules-general-functions.php:82 Array ( [0] => Array ( [file] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [line] => 82 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "mysql_identifier_quote_character" [2] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [3] => 82 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/includes/database/mysql/database.inc [line] => 397 [function] => variable_get [args] => Array ( [0] => mysql_identifier_quote_character [1] => ` ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/includes/database/database.inc [line] => 329 [function] => setPrefix [class] => DatabaseConnection_mysql [object] => DatabaseConnection_mysql Object ( [target:protected] => [key:protected] => [logger:protected] => [transactionLayers:protected] => Array ( ) [driverClasses:protected] => Array ( ) [statementClass:protected] => DatabaseStatementBase [transactionSupport:protected] => 1 [transactionalDDLSupport:protected] => [temporaryNameIndex:protected] => 0 [connection:protected] => [connectionOptions:protected] => Array ( [driver] => mysql [database] => hitrahr [username] => root [password] => asdf [host] => localhost [prefix] => Array ( [default] => ) ) [schema:protected] => [prefixes:protected] => Array ( [default] => ) [prefixSearch:protected] => Array ( [0] => { [1] => } ) [prefixReplace:protected] => Array ( [0] => [1] => ) [escapedNames:protected] => Array ( ) [escapedAliases:protected] => Array ( ) [unprefixedTablesMap:protected] => Array ( ) [needsCleanup:protected] => [reservedKeyWords:DatabaseConnection_mysql:private] => Array ( [0] => accessible [1] => add [2] => admin [3] => all [4] => alter [5] => analyze [6] => and [7] => as [8] => asc [9] => asensitive [10] => before [11] => between [12] => bigint [13] => binary [14] => blob [15] => both [16] => by [17] => call [18] => cascade [19] => case [20] => change [21] => char [22] => character [23] => check [24] => collate [25] => column [26] => condition [27] => constraint [28] => continue [29] => convert [30] => create [31] => cross [32] => cube [33] => cume_dist [34] => current_date [35] => current_time [36] => current_timestamp [37] => current_user [38] => cursor [39] => database [40] => databases [41] => day_hour [42] => day_microsecond [43] => day_minute [44] => day_second [45] => dec [46] => decimal [47] => declare [48] => default [49] => delayed [50] => delete [51] => dense_rank [52] => desc [53] => describe [54] => deterministic [55] => distinct [56] => distinctrow [57] => div [58] => double [59] => drop [60] => dual [61] => each [62] => else [63] => elseif [64] => empty [65] => enclosed [66] => escaped [67] => except [68] => exists [69] => exit [70] => explain [71] => false [72] => fetch [73] => first_value [74] => float [75] => float4 [76] => float8 [77] => for [78] => force [79] => foreign [80] => from [81] => fulltext [82] => function [83] => generated [84] => get [85] => grant [86] => group [87] => grouping [88] => groups [89] => having [90] => high_priority [91] => hour_microsecond [92] => hour_minute [93] => hour_second [94] => if [95] => ignore [96] => in [97] => index [98] => infile [99] => inner [100] => inout [101] => insensitive [102] => insert [103] => int [104] => int1 [105] => int2 [106] => int3 [107] => int4 [108] => int8 [109] => integer [110] => intersect [111] => interval [112] => into [113] => io_after_gtids [114] => io_before_gtids [115] => is [116] => iterate [117] => join [118] => json_table [119] => key [120] => keys [121] => kill [122] => lag [123] => last_value [124] => lateral [125] => lead [126] => leading [127] => leave [128] => left [129] => like [130] => limit [131] => linear [132] => lines [133] => load [134] => localtime [135] => localtimestamp [136] => lock [137] => long [138] => longblob [139] => longtext [140] => loop [141] => low_priority [142] => master_bind [143] => master_ssl_verify_server_cert [144] => match [145] => maxvalue [146] => mediumblob [147] => mediumint [148] => mediumtext [149] => middleint [150] => minute_microsecond [151] => minute_second [152] => mod [153] => modifies [154] => natural [155] => not [156] => no_write_to_binlog [157] => nth_value [158] => ntile [159] => null [160] => numeric [161] => of [162] => on [163] => optimize [164] => optimizer_costs [165] => option [166] => optionally [167] => or [168] => order [169] => out [170] => outer [171] => outfile [172] => over [173] => partition [174] => percent_rank [175] => persist [176] => persist_only [177] => precision [178] => primary [179] => procedure [180] => purge [181] => range [182] => rank [183] => read [184] => reads [185] => read_write [186] => real [187] => recursive [188] => references [189] => regexp [190] => release [191] => rename [192] => repeat [193] => replace [194] => require [195] => resignal [196] => restrict [197] => return [198] => revoke [199] => right [200] => rlike [201] => row [202] => rows [203] => row_number [204] => schema [205] => schemas [206] => second_microsecond [207] => select [208] => sensitive [209] => separator [210] => set [211] => show [212] => signal [213] => smallint [214] => spatial [215] => specific [216] => sql [217] => sqlexception [218] => sqlstate [219] => sqlwarning [220] => sql_big_result [221] => sql_calc_found_rows [222] => sql_small_result [223] => ssl [224] => starting [225] => stored [226] => straight_join [227] => system [228] => table [229] => terminated [230] => then [231] => tinyblob [232] => tinyint [233] => tinytext [234] => to [235] => trailing [236] => trigger [237] => true [238] => undo [239] => union [240] => unique [241] => unlock [242] => unsigned [243] => update [244] => usage [245] => use [246] => using [247] => utc_date [248] => utc_time [249] => utc_timestamp [250] => values [251] => varbinary [252] => varchar [253] => varcharacter [254] => varying [255] => virtual [256] => when [257] => where [258] => while [259] => window [260] => with [261] => write [262] => xor [263] => year_month [264] => zerofill ) ) [type] => -> [args] => Array ( [0] => Array ( [default] => ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/includes/database/mysql/database.inc [line] => 349 [function] => __construct [class] => DatabaseConnection [object] => DatabaseConnection_mysql Object ( [target:protected] => [key:protected] => [logger:protected] => [transactionLayers:protected] => Array ( ) [driverClasses:protected] => Array ( ) [statementClass:protected] => DatabaseStatementBase [transactionSupport:protected] => 1 [transactionalDDLSupport:protected] => [temporaryNameIndex:protected] => 0 [connection:protected] => [connectionOptions:protected] => Array ( [driver] => mysql [database] => hitrahr [username] => root [password] => asdf [host] => localhost [prefix] => Array ( [default] => ) ) [schema:protected] => [prefixes:protected] => Array ( [default] => ) [prefixSearch:protected] => Array ( [0] => { [1] => } ) [prefixReplace:protected] => Array ( [0] => [1] => ) [escapedNames:protected] => Array ( ) [escapedAliases:protected] => Array ( ) [unprefixedTablesMap:protected] => Array ( ) [needsCleanup:protected] => [reservedKeyWords:DatabaseConnection_mysql:private] => Array ( [0] => accessible [1] => add [2] => admin [3] => all [4] => alter [5] => analyze [6] => and [7] => as [8] => asc [9] => asensitive [10] => before [11] => between [12] => bigint [13] => binary [14] => blob [15] => both [16] => by [17] => call [18] => cascade [19] => case [20] => change [21] => char [22] => character [23] => check [24] => collate [25] => column [26] => condition [27] => constraint [28] => continue [29] => convert [30] => create [31] => cross [32] => cube [33] => cume_dist [34] => current_date [35] => current_time [36] => current_timestamp [37] => current_user [38] => cursor [39] => database [40] => databases [41] => day_hour [42] => day_microsecond [43] => day_minute [44] => day_second [45] => dec [46] => decimal [47] => declare [48] => default [49] => delayed [50] => delete [51] => dense_rank [52] => desc [53] => describe [54] => deterministic [55] => distinct [56] => distinctrow [57] => div [58] => double [59] => drop [60] => dual [61] => each [62] => else [63] => elseif [64] => empty [65] => enclosed [66] => escaped [67] => except [68] => exists [69] => exit [70] => explain [71] => false [72] => fetch [73] => first_value [74] => float [75] => float4 [76] => float8 [77] => for [78] => force [79] => foreign [80] => from [81] => fulltext [82] => function [83] => generated [84] => get [85] => grant [86] => group [87] => grouping [88] => groups [89] => having [90] => high_priority [91] => hour_microsecond [92] => hour_minute [93] => hour_second [94] => if [95] => ignore [96] => in [97] => index [98] => infile [99] => inner [100] => inout [101] => insensitive [102] => insert [103] => int [104] => int1 [105] => int2 [106] => int3 [107] => int4 [108] => int8 [109] => integer [110] => intersect [111] => interval [112] => into [113] => io_after_gtids [114] => io_before_gtids [115] => is [116] => iterate [117] => join [118] => json_table [119] => key [120] => keys [121] => kill [122] => lag [123] => last_value [124] => lateral [125] => lead [126] => leading [127] => leave [128] => left [129] => like [130] => limit [131] => linear [132] => lines [133] => load [134] => localtime [135] => localtimestamp [136] => lock [137] => long [138] => longblob [139] => longtext [140] => loop [141] => low_priority [142] => master_bind [143] => master_ssl_verify_server_cert [144] => match [145] => maxvalue [146] => mediumblob [147] => mediumint [148] => mediumtext [149] => middleint [150] => minute_microsecond [151] => minute_second [152] => mod [153] => modifies [154] => natural [155] => not [156] => no_write_to_binlog [157] => nth_value [158] => ntile [159] => null [160] => numeric [161] => of [162] => on [163] => optimize [164] => optimizer_costs [165] => option [166] => optionally [167] => or [168] => order [169] => out [170] => outer [171] => outfile [172] => over [173] => partition [174] => percent_rank [175] => persist [176] => persist_only [177] => precision [178] => primary [179] => procedure [180] => purge [181] => range [182] => rank [183] => read [184] => reads [185] => read_write [186] => real [187] => recursive [188] => references [189] => regexp [190] => release [191] => rename [192] => repeat [193] => replace [194] => require [195] => resignal [196] => restrict [197] => return [198] => revoke [199] => right [200] => rlike [201] => row [202] => rows [203] => row_number [204] => schema [205] => schemas [206] => second_microsecond [207] => select [208] => sensitive [209] => separator [210] => set [211] => show [212] => signal [213] => smallint [214] => spatial [215] => specific [216] => sql [217] => sqlexception [218] => sqlstate [219] => sqlwarning [220] => sql_big_result [221] => sql_calc_found_rows [222] => sql_small_result [223] => ssl [224] => starting [225] => stored [226] => straight_join [227] => system [228] => table [229] => terminated [230] => then [231] => tinyblob [232] => tinyint [233] => tinytext [234] => to [235] => trailing [236] => trigger [237] => true [238] => undo [239] => union [240] => unique [241] => unlock [242] => unsigned [243] => update [244] => usage [245] => use [246] => using [247] => utc_date [248] => utc_time [249] => utc_timestamp [250] => values [251] => varbinary [252] => varchar [253] => varcharacter [254] => varying [255] => virtual [256] => when [257] => where [258] => while [259] => window [260] => with [261] => write [262] => xor [263] => year_month [264] => zerofill ) ) [type] => -> [args] => Array ( [0] => mysql:host=localhost;port=3306;charset=utf8;dbname=hitrahr [1] => root [2] => asdf [3] => Array ( [1000] => 1 [20] => 1 [17] => 1 [1013] => ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/includes/database/database.inc [line] => 1796 [function] => __construct [class] => DatabaseConnection_mysql [object] => DatabaseConnection_mysql Object ( [target:protected] => [key:protected] => [logger:protected] => [transactionLayers:protected] => Array ( ) [driverClasses:protected] => Array ( ) [statementClass:protected] => DatabaseStatementBase [transactionSupport:protected] => 1 [transactionalDDLSupport:protected] => [temporaryNameIndex:protected] => 0 [connection:protected] => [connectionOptions:protected] => Array ( [driver] => mysql [database] => hitrahr [username] => root [password] => asdf [host] => localhost [prefix] => Array ( [default] => ) ) [schema:protected] => [prefixes:protected] => Array ( [default] => ) [prefixSearch:protected] => Array ( [0] => { [1] => } ) [prefixReplace:protected] => Array ( [0] => [1] => ) [escapedNames:protected] => Array ( ) [escapedAliases:protected] => Array ( ) [unprefixedTablesMap:protected] => Array ( ) [needsCleanup:protected] => [reservedKeyWords:DatabaseConnection_mysql:private] => Array ( [0] => accessible [1] => add [2] => admin [3] => all [4] => alter [5] => analyze [6] => and [7] => as [8] => asc [9] => asensitive [10] => before [11] => between [12] => bigint [13] => binary [14] => blob [15] => both [16] => by [17] => call [18] => cascade [19] => case [20] => change [21] => char [22] => character [23] => check [24] => collate [25] => column [26] => condition [27] => constraint [28] => continue [29] => convert [30] => create [31] => cross [32] => cube [33] => cume_dist [34] => current_date [35] => current_time [36] => current_timestamp [37] => current_user [38] => cursor [39] => database [40] => databases [41] => day_hour [42] => day_microsecond [43] => day_minute [44] => day_second [45] => dec [46] => decimal [47] => declare [48] => default [49] => delayed [50] => delete [51] => dense_rank [52] => desc [53] => describe [54] => deterministic [55] => distinct [56] => distinctrow [57] => div [58] => double [59] => drop [60] => dual [61] => each [62] => else [63] => elseif [64] => empty [65] => enclosed [66] => escaped [67] => except [68] => exists [69] => exit [70] => explain [71] => false [72] => fetch [73] => first_value [74] => float [75] => float4 [76] => float8 [77] => for [78] => force [79] => foreign [80] => from [81] => fulltext [82] => function [83] => generated [84] => get [85] => grant [86] => group [87] => grouping [88] => groups [89] => having [90] => high_priority [91] => hour_microsecond [92] => hour_minute [93] => hour_second [94] => if [95] => ignore [96] => in [97] => index [98] => infile [99] => inner [100] => inout [101] => insensitive [102] => insert [103] => int [104] => int1 [105] => int2 [106] => int3 [107] => int4 [108] => int8 [109] => integer [110] => intersect [111] => interval [112] => into [113] => io_after_gtids [114] => io_before_gtids [115] => is [116] => iterate [117] => join [118] => json_table [119] => key [120] => keys [121] 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[function] => category_validate_url_alias [args] => Array ( [0] => cc ) ) [10] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 86 [function] => check_for_module [args] => Array ( [0] => /cc/firefly [1] => Array ( [0] => [1] => cc [2] => firefly ) ) ) [11] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [12] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => firefly [1] => ) ) [2] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-functions.php [line] => 38 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => firefly [hr_nid] => 472879 [title] => Adobe Firefly: Generative AI for Creatives [requirements] =>

Audience

[overview] =>

Adobe Firefly is a product and a model that uses generative AI to create images, text effects, and color palettes from simple text prompts.

This instructor-led, live training (online or onsite) is aimed at beginner-level designers, artists, and content creators who wish to use Adobe Firefly to enhance their creativity and productivity.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at beginner-level designers, artists, and content creators who wish to use Adobe Firefly to enhance their creativity and productivity.

By the end of this training, participants will be able to:

[outline] =>

Introduction

Creating Images with Adobe Firefly

Creating Text Effects and Color Palettes with Adobe Firefly

Generating Safe Content for Commercial Use

Applying Ethical Principles to Generative AI Use

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1709063812 [source_title] => Adobe Firefly: Generative AI for Creatives [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => firefly [hr_nid] => 472879 [title] => Adobe Firefly: Generative AI for Creatives [requirements] =>

Audiencia

[overview] =>

Adobe Firefly es un producto y un modelo que utiliza IA generativa para crear imágenes, efectos de texto y paletas de colores a partir de simples indicaciones de texto.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introducción

Creación de imágenes con Adobe Firefly

Creación de efectos de texto y paletas de colores con Adobe Firefly

Generación de contenido seguro para uso comercial

Aplicación de principios éticos al uso de la IA generativa

Resumen y próximos pasos

[language] => es [duration] => 14 [status] => published [changed] => 1709063812 [source_title] => Adobe Firefly: Generative AI for Creatives [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) ) ) ) [3] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 150 [function] => hrquery_outline_load_all_v2 [args] => Array ( [0] => firefly ) ) [4] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 13 [function] => course_get_outline [args] => Array ( [0] => firefly ) ) [5] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [6] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [7] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [8] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "mysql_identifier_quote_character" /apps/nobleprog-website/includes/functions/new-modules-general-functions.php:82 Array ( [0] => Array ( [file] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [line] => 82 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "mysql_identifier_quote_character" [2] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [3] => 82 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/includes/database/mysql/database.inc [line] => 397 [function] => variable_get [args] => Array ( [0] => mysql_identifier_quote_character [1] => ` ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/includes/database/database.inc [line] => 329 [function] => setPrefix [class] => DatabaseConnection_mysql [object] => DatabaseConnection_mysql Object ( [target:protected] => [key:protected] => [logger:protected] => [transactionLayers:protected] => Array ( ) [driverClasses:protected] => Array ( ) [statementClass:protected] => DatabaseStatementBase [transactionSupport:protected] => 1 [transactionalDDLSupport:protected] => [temporaryNameIndex:protected] => 0 [connection:protected] => [connectionOptions:protected] => Array ( [driver] => mysql [database] => common_fe [username] => root [password] => asdf [host] => localhost [prefix] => Array ( [default] => ) ) [schema:protected] => [prefixes:protected] => Array ( [default] => ) [prefixSearch:protected] => Array ( [0] => { [1] => } ) [prefixReplace:protected] => Array ( [0] => [1] => ) [escapedNames:protected] => Array ( ) [escapedAliases:protected] => Array ( ) [unprefixedTablesMap:protected] => Array ( ) [needsCleanup:protected] => [reservedKeyWords:DatabaseConnection_mysql:private] => Array ( [0] => accessible [1] => add [2] => admin [3] => all [4] => alter [5] => analyze [6] => and [7] => as [8] => asc [9] => asensitive [10] => before [11] => between [12] => bigint [13] => binary [14] => blob [15] => both [16] => by [17] => call [18] => cascade [19] => case [20] => change [21] => char [22] => character [23] => check [24] => collate [25] => column [26] => condition [27] => constraint [28] => continue [29] => convert [30] => create [31] => cross [32] => cube [33] => cume_dist [34] => current_date [35] => current_time [36] => current_timestamp [37] => current_user [38] => cursor [39] => database [40] => databases [41] => day_hour [42] => day_microsecond [43] => day_minute [44] => day_second [45] => dec [46] => decimal [47] => declare [48] => default [49] => delayed [50] => delete [51] => dense_rank [52] => desc [53] => describe [54] => deterministic [55] => distinct [56] => distinctrow [57] => div [58] => double [59] => drop [60] => dual [61] => each [62] => else [63] => elseif [64] => empty [65] => enclosed [66] => escaped [67] => except [68] => exists [69] => exit [70] => explain [71] => false [72] => fetch [73] => first_value [74] => float [75] => float4 [76] => float8 [77] => for [78] => force [79] => foreign [80] => from [81] => fulltext [82] => function [83] => generated [84] => get [85] => grant [86] => group [87] => grouping [88] => groups [89] => having [90] => high_priority [91] => hour_microsecond [92] => hour_minute [93] => hour_second [94] => if [95] => ignore [96] => in [97] => index [98] => infile [99] => inner [100] => inout [101] => insensitive [102] => insert [103] => int [104] => int1 [105] => int2 [106] => int3 [107] => int4 [108] => int8 [109] => integer [110] => intersect [111] => interval [112] => into [113] => io_after_gtids [114] => io_before_gtids [115] => is [116] => iterate [117] => join [118] => json_table [119] => key [120] => keys [121] => kill [122] => lag [123] => last_value [124] => lateral [125] => lead [126] => leading [127] => leave [128] => left [129] => like [130] => limit [131] => linear [132] => lines [133] => load [134] => localtime [135] => localtimestamp [136] => lock [137] => long [138] => longblob [139] => longtext [140] => loop [141] => low_priority [142] => master_bind [143] => master_ssl_verify_server_cert [144] => match [145] => maxvalue [146] => mediumblob [147] => mediumint [148] => mediumtext [149] => middleint [150] => minute_microsecond [151] => minute_second [152] => mod [153] => modifies [154] => natural [155] => not [156] => no_write_to_binlog [157] => nth_value [158] => ntile [159] => null [160] => numeric [161] => of [162] => on [163] => optimize [164] => optimizer_costs [165] => option [166] => optionally [167] => or [168] => order [169] => out [170] => outer [171] => outfile [172] => over [173] => partition [174] => percent_rank [175] => persist [176] => persist_only [177] => precision [178] => primary [179] => procedure [180] => purge [181] => range [182] => rank [183] => read [184] => reads [185] => read_write [186] => real [187] => recursive [188] => references [189] => regexp [190] => release [191] => rename [192] => repeat [193] => replace [194] => require [195] => resignal [196] => restrict [197] => return [198] => revoke [199] => right [200] => rlike [201] => row [202] => rows [203] => row_number [204] => schema [205] => schemas [206] => second_microsecond [207] => select [208] => sensitive [209] => separator [210] => set [211] => show [212] => signal [213] => smallint [214] => spatial [215] => specific [216] => sql [217] => sqlexception [218] => sqlstate [219] => sqlwarning [220] => sql_big_result [221] => sql_calc_found_rows [222] => sql_small_result [223] => ssl [224] => starting [225] => stored [226] => straight_join [227] => system [228] => table [229] => terminated [230] => then [231] => tinyblob [232] => tinyint [233] => tinytext [234] => to [235] => trailing [236] => trigger [237] => true [238] => undo [239] => union [240] => unique [241] => unlock [242] => unsigned [243] => update [244] => usage [245] => use [246] => using [247] => utc_date [248] => utc_time [249] => utc_timestamp [250] => values [251] => varbinary [252] => varchar [253] => varcharacter [254] => varying [255] => virtual [256] => when [257] => where [258] => while [259] => window [260] => with [261] => write [262] => xor [263] => year_month [264] => zerofill ) ) [type] => -> [args] => Array ( [0] => Array ( [default] => ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/includes/database/mysql/database.inc [line] => 349 [function] => __construct [class] => DatabaseConnection [object] => DatabaseConnection_mysql Object ( [target:protected] => [key:protected] => [logger:protected] => [transactionLayers:protected] => Array ( ) [driverClasses:protected] => Array ( ) [statementClass:protected] => DatabaseStatementBase [transactionSupport:protected] => 1 [transactionalDDLSupport:protected] => [temporaryNameIndex:protected] => 0 [connection:protected] => [connectionOptions:protected] => Array ( [driver] => mysql [database] => common_fe [username] => root [password] => asdf [host] => localhost [prefix] => Array ( [default] => ) ) [schema:protected] => [prefixes:protected] => Array ( [default] => ) [prefixSearch:protected] => Array ( [0] => { [1] => } ) [prefixReplace:protected] => Array ( [0] => [1] => ) [escapedNames:protected] => Array ( ) [escapedAliases:protected] => Array ( ) [unprefixedTablesMap:protected] => Array ( ) [needsCleanup:protected] => [reservedKeyWords:DatabaseConnection_mysql:private] => Array ( [0] => accessible [1] => add [2] => admin [3] => all [4] => alter [5] => analyze [6] => and [7] => as [8] => asc [9] => asensitive [10] => before [11] => between [12] => bigint [13] => binary [14] => blob [15] => both [16] => by [17] => call [18] => cascade [19] => case [20] => change [21] => char [22] => character [23] => check [24] => collate [25] => column [26] => condition [27] => constraint [28] => continue [29] => convert [30] => create [31] => cross [32] => cube [33] => cume_dist [34] => current_date [35] => current_time [36] => current_timestamp [37] => current_user [38] => cursor [39] => database [40] => databases [41] => day_hour [42] => day_microsecond [43] => day_minute [44] => day_second [45] => dec [46] => decimal [47] => declare [48] => default [49] => delayed [50] => delete [51] => dense_rank [52] => desc [53] => describe [54] => deterministic [55] => distinct [56] => distinctrow [57] => div [58] => double [59] => drop [60] => dual [61] => each [62] => else [63] => elseif [64] => empty [65] => enclosed [66] => escaped [67] => except [68] => exists [69] => exit [70] => explain [71] => false [72] => fetch [73] => first_value [74] => float [75] => float4 [76] => float8 [77] => for [78] => force [79] => foreign [80] => from [81] => fulltext [82] => function [83] => generated [84] => get [85] => grant [86] => group [87] => grouping [88] => groups [89] => having [90] => high_priority [91] => hour_microsecond [92] => hour_minute [93] => hour_second [94] => if [95] => ignore [96] => in [97] => index [98] => infile [99] => inner [100] => inout [101] => insensitive [102] => insert [103] => int [104] => int1 [105] => int2 [106] => int3 [107] => int4 [108] => int8 [109] => integer [110] => intersect [111] => interval [112] => into [113] => io_after_gtids [114] => io_before_gtids [115] => is [116] => iterate [117] => join [118] => json_table [119] => key [120] => keys [121] => kill [122] => lag [123] => last_value [124] => lateral [125] => lead [126] => leading [127] => leave [128] => left [129] => like [130] => limit [131] => linear [132] => lines [133] => load [134] => localtime [135] => localtimestamp [136] => lock [137] => long [138] => longblob [139] => longtext [140] => loop [141] => low_priority [142] => master_bind [143] => master_ssl_verify_server_cert [144] => match [145] => maxvalue [146] => mediumblob [147] => mediumint [148] => mediumtext [149] => middleint [150] => minute_microsecond [151] => minute_second [152] => mod [153] => modifies [154] => natural [155] => not [156] => no_write_to_binlog [157] => nth_value [158] => ntile [159] => null [160] => numeric [161] => of [162] => on [163] => optimize [164] => optimizer_costs [165] => option [166] => optionally [167] => or [168] => order [169] => out [170] => outer [171] => outfile [172] => over [173] => partition [174] => percent_rank [175] => persist [176] => persist_only [177] => precision [178] => primary [179] => procedure [180] => purge [181] => range [182] => rank [183] => read [184] => reads [185] => read_write [186] => real [187] => recursive [188] => references [189] => regexp [190] => release [191] => rename [192] => repeat [193] => replace [194] => require [195] => resignal [196] => restrict [197] => return [198] => revoke [199] => right [200] => rlike [201] => row [202] => rows [203] => row_number [204] => schema [205] => schemas [206] => second_microsecond [207] => select [208] => sensitive [209] => separator [210] => set [211] => show [212] => signal [213] => smallint [214] => spatial [215] => specific [216] => sql [217] => sqlexception [218] => sqlstate [219] => sqlwarning [220] => sql_big_result [221] => sql_calc_found_rows [222] => sql_small_result [223] => ssl [224] => starting [225] => stored [226] => straight_join [227] => system [228] => table [229] => terminated [230] => then [231] => tinyblob [232] => tinyint [233] => tinytext [234] => to [235] => trailing [236] => trigger [237] => true [238] => undo [239] => union [240] => unique [241] => unlock [242] => unsigned [243] => update [244] => usage [245] => use [246] => using [247] => utc_date [248] => utc_time [249] => utc_timestamp [250] => values [251] => varbinary [252] => varchar [253] => varcharacter [254] => varying [255] => virtual [256] => when [257] => where [258] => while [259] => window [260] => with [261] => write [262] => xor [263] => year_month [264] => zerofill ) ) [type] => -> [args] => Array ( [0] => mysql:host=localhost;port=3306;charset=utf8;dbname=common_fe [1] => root [2] => asdf [3] => Array ( [1000] => 1 [20] => 1 [17] => 1 [1013] => ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/includes/database/database.inc [line] => 1796 [function] => __construct [class] => DatabaseConnection_mysql [object] => DatabaseConnection_mysql Object ( [target:protected] => [key:protected] => [logger:protected] => [transactionLayers:protected] => Array ( ) [driverClasses:protected] => Array ( ) [statementClass:protected] => DatabaseStatementBase [transactionSupport:protected] => 1 [transactionalDDLSupport:protected] => [temporaryNameIndex:protected] => 0 [connection:protected] => [connectionOptions:protected] => Array ( [driver] => mysql [database] => common_fe [username] => root [password] => asdf [host] => localhost [prefix] => Array ( [default] => ) ) [schema:protected] => [prefixes:protected] => Array ( [default] => ) [prefixSearch:protected] => Array ( [0] => { [1] => } ) [prefixReplace:protected] => Array ( [0] => [1] => ) [escapedNames:protected] => Array ( ) [escapedAliases:protected] => Array ( ) [unprefixedTablesMap:protected] => Array ( ) [needsCleanup:protected] => [reservedKeyWords:DatabaseConnection_mysql:private] => Array ( [0] => accessible [1] => add [2] => admin [3] => all [4] => alter [5] => analyze [6] => and [7] => as [8] => asc [9] => asensitive [10] => before [11] => between [12] => bigint [13] => binary [14] => blob [15] => both [16] => by [17] => call [18] => cascade [19] => case [20] => change [21] => char [22] => character [23] => check [24] => collate [25] => column [26] => condition [27] => constraint [28] => continue [29] => convert [30] => create [31] => cross [32] => cube [33] => cume_dist [34] => current_date [35] => current_time [36] => current_timestamp [37] => current_user [38] => cursor [39] => database [40] => databases [41] => day_hour [42] => day_microsecond [43] => day_minute [44] => day_second [45] => dec [46] => decimal [47] => declare [48] => default [49] => delayed [50] => delete [51] => dense_rank [52] => desc [53] => describe [54] => deterministic [55] => distinct [56] => distinctrow [57] => div [58] => double [59] => drop [60] => dual [61] => each [62] => else [63] => elseif [64] => empty [65] => enclosed [66] => escaped [67] => except [68] => exists [69] => exit [70] => explain [71] => false [72] => fetch [73] => first_value [74] => float [75] => float4 [76] => float8 [77] => for [78] => force [79] => foreign [80] => from [81] => fulltext [82] => function [83] => generated [84] => get [85] => grant [86] => group [87] => grouping [88] => groups [89] => having [90] => high_priority [91] => hour_microsecond [92] => hour_minute [93] => hour_second [94] => if [95] => ignore [96] => in [97] => index [98] => infile [99] => inner [100] => inout [101] => insensitive [102] => insert [103] => int [104] => int1 [105] => int2 [106] => int3 [107] => int4 [108] => int8 [109] => integer [110] => intersect [111] => interval [112] => into [113] => io_after_gtids [114] => io_before_gtids [115] => is [116] => iterate [117] => join [118] => json_table [119] => key [120] => keys [121] => kill [122] => lag [123] => last_value [124] => lateral [125] => lead [126] => leading [127] => leave [128] => left [129] => like [130] => limit [131] => linear [132] => lines [133] => load [134] => localtime [135] => localtimestamp [136] => lock [137] => long [138] => longblob [139] => longtext [140] => loop [141] => low_priority [142] => master_bind [143] => master_ssl_verify_server_cert [144] => match [145] => maxvalue [146] => mediumblob [147] => mediumint [148] => mediumtext [149] => middleint [150] => minute_microsecond [151] => minute_second [152] => mod [153] => modifies [154] => natural [155] => not [156] => no_write_to_binlog [157] => nth_value [158] => ntile [159] => null [160] => numeric [161] => of [162] => on [163] => optimize [164] => optimizer_costs [165] => option [166] => optionally [167] => or [168] => order [169] => out [170] => outer [171] => outfile [172] => over [173] => partition [174] => percent_rank [175] => persist [176] => persist_only [177] => precision [178] => primary [179] => procedure [180] => purge [181] => range [182] => rank [183] => read [184] => reads [185] => read_write [186] => real [187] => recursive [188] => references [189] => regexp [190] => release [191] => rename [192] => repeat [193] => replace [194] => require [195] => resignal [196] => restrict [197] => return [198] => revoke [199] => right [200] => rlike [201] => row [202] => rows [203] => row_number [204] => schema [205] => schemas [206] => second_microsecond [207] => select [208] => sensitive [209] => separator [210] => set [211] => show [212] => signal [213] => smallint [214] => spatial [215] => specific [216] => sql [217] => sqlexception [218] => sqlstate [219] => sqlwarning [220] => sql_big_result [221] => sql_calc_found_rows [222] => sql_small_result [223] => ssl [224] => starting [225] => stored [226] => straight_join [227] => system [228] => table [229] => terminated [230] => then [231] => tinyblob [232] => tinyint [233] => tinytext [234] => to [235] => trailing [236] => trigger [237] => true [238] => undo [239] => union [240] => unique [241] => unlock [242] => unsigned [243] => update [244] => usage [245] => use [246] => using [247] => utc_date [248] => utc_time [249] => utc_timestamp [250] => values [251] => varbinary [252] => varchar [253] => varcharacter [254] => varying [255] => virtual [256] => when [257] => where [258] => while [259] => window [260] => with [261] => write [262] => xor [263] => year_month [264] => zerofill ) ) [type] => -> [args] => Array ( [0] => Array ( [driver] => mysql [database] => common_fe [username] => root [password] => asdf [host] => localhost [prefix] => Array ( [default] => ) [pdo] => Array ( [1000] => 1 [20] => 1 [17] => 1 [1013] => ) ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/includes/database/database.inc [line] => 1582 [function] => openConnection [class] => Database [type] => :: [args] => Array ( [0] => common_fe [1] => default ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/includes/database/database.inc [line] => 2467 [function] => getConnection [class] => Database [type] => :: [args] => Array ( [0] => default ) ) [7] => Array ( [file] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [line] => 31 [function] => db_query [args] => Array ( [0] => SELECT * FROM price_formulas WHERE country_code = :country_code [1] => Array ( [:country_code] => ve ) ) ) [8] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 111 [function] => np_db_query [args] => Array ( [0] => common_fe [1] => db_query [2] => SELECT * FROM price_formulas WHERE country_code = :country_code [3] => Array ( [:country_code] => ve ) ) ) [9] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 93 [function] => get_formula [args] => Array ( [0] => ve ) ) [10] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 355 [function] => course_price_v2_formula [args] => Array ( ) ) [11] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 344 [function] => course_price_change_to_fe_p [args] => Array ( [0] => firefly [1] => 14 [2] => [3] => 0 [4] => [5] => USD ) ) [12] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 316 [function] => course_price_get_default_price [args] => Array ( [0] => firefly ) ) [13] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 15 [function] => course_price_get_price [args] => Array ( [0] => firefly ) ) [14] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 23 [function] => course_price_virtual_event_price [args] => Array ( [0] => firefly ) ) [15] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [16] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [17] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [18] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "sdp" /apps/nobleprog-website/includes/functions/course-prices.php:281 Array ( [0] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 281 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "sdp" [2] => /apps/nobleprog-website/includes/functions/course-prices.php [3] => 281 ) ) [1] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 45 [function] => course_price_table [args] => Array ( [0] => Array ( [fdp] => 3150 [adp] => 750 [reduced_fdp] => [reduced_adp] => [days] => 2 [default_venue_fdc] => 350 [default_venue_adc] => 50 [people] => 1 [hours] => 14 [course_code] => firefly [venue_id] => ve_10638169 [vfdc] => 250.00 [vadc] => 75.00 ) [1] => 10 ) ) [2] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 23 [function] => course_price_virtual_event_price [args] => Array ( [0] => firefly ) ) [3] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [4] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [5] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [6] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "nobleprog_default_trainer_journey" /apps/nobleprog-website/includes/functions/course-prices.php:286 Array ( [0] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 286 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "nobleprog_default_trainer_journey" [2] => /apps/nobleprog-website/includes/functions/course-prices.php [3] => 286 ) ) [1] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 45 [function] => course_price_table [args] => Array ( [0] => Array ( [fdp] => 3150 [adp] => 750 [reduced_fdp] => [reduced_adp] => [days] => 2 [default_venue_fdc] => 350 [default_venue_adc] => 50 [people] => 1 [hours] => 14 [course_code] => firefly [venue_id] => ve_10638169 [vfdc] => 250.00 [vadc] => 75.00 ) [1] => 10 ) ) [2] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 23 [function] => course_price_virtual_event_price [args] => Array ( [0] => firefly ) ) [3] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [4] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [5] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [6] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "nobleprog_price_rounding" /apps/nobleprog-website/includes/functions/course-prices.php:289 Array ( [0] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 289 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "nobleprog_price_rounding" [2] => /apps/nobleprog-website/includes/functions/course-prices.php [3] => 289 ) ) [1] => Array ( [file] => /apps/nobleprog-website/includes/functions/course-prices.php [line] => 45 [function] => course_price_table [args] => Array ( [0] => Array ( [fdp] => 3150 [adp] => 750 [reduced_fdp] => [reduced_adp] => [days] => 2 [default_venue_fdc] => 350 [default_venue_adc] => 50 [people] => 1 [hours] => 14 [course_code] => firefly [venue_id] => ve_10638169 [vfdc] => 250.00 [vadc] => 75.00 ) [1] => 10 ) ) [2] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 23 [function] => course_price_virtual_event_price [args] => Array ( [0] => firefly ) ) [3] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [4] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [5] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [6] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => langchain [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => langchain [hr_nid] => 476371 [title] => LangChain: Building AI-Powered Applications [requirements] =>

Audience

[overview] =>

LangChain is an open-source framework designed to facilitate the development of applications using large language models (LLMs).

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build AI-powered applications using the LangChain framework.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build AI-powered applications using the LangChain framework.

By the end of this training, participants will be able to:

[outline] =>

Introduction to LangChain

Understanding Large Language Models (LLMs)

LangChain Components and Architecture

Integrating LangChain with LLMs

Building Modular Applications

Practical Exercises with LangChain

Advanced LangChain Features

Best Practices and Patterns

Troubleshooting

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712088649 [source_title] => LangChain: Building AI-Powered Applications [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => langchain [hr_nid] => 476371 [title] => LangChain: Building AI-Powered Applications [requirements] => [overview] =>

LangChain es un marco de código abierto diseñado para facilitar el desarrollo de aplicaciones utilizando grandes modelos de lenguaje (LLM).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 14 [status] => published [changed] => 1712088649 [source_title] => LangChain: Building AI-Powered Applications [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => langchain [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => langchain [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => langchainfun [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => langchainfun [hr_nid] => 476375 [title] => LangChain Fundamentals [requirements] =>

Audience

[overview] =>

LangChain is an open-source framework that simplifies the integration of large language models (LLMs) into applications.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the practical skills for building AI-powered applications.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the practical skills for building AI-powered applications.

By the end of this training, participants will be able to:

[outline] =>

Introduction to LangChain

Setting Up the Environment

Core Concepts of LangChain

Working with Large Language Models (LLMs)

Developing with LangChain

Troubleshooting

Conclusion and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712091756 [source_title] => LangChain Fundamentals [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => langchainfun [hr_nid] => 476375 [title] => LangChain Fundamentals [requirements] => [overview] =>

LangChain es un marco de código abierto que simplifica la integración de grandes modelos de lenguaje (LLM) en las aplicaciones.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 14 [status] => published [changed] => 1712091756 [source_title] => LangChain Fundamentals [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => 1 ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => langchainfun [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => langchainfun [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => slms [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => slms [hr_nid] => 479495 [title] => Small Language Models (SLMs): Applications and Innovations [requirements] =>

Audience

[overview] =>

Small Language Models (SLMs) are a cutting-edge subset of AI that enables efficient language processing on devices with limited computational resources.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level data scientists and developers who wish to implement and leverage Small Language Models in various applications.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at beginner-level to intermediate-level data scientists and developers who wish to implement and leverage Small Language Models in various applications.

By the end of this training, participants will be able to:

[outline] =>

Introduction to Small Language Models (SLMs)

Technical Foundations

SLMs in Natural Language Processing

Real-world Applications of SLMs

Case Studies

Future Directions

Hands-on Workshops

Capstone Project

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715280132 [source_title] => Small Language Models (SLMs): Applications and Innovations [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => slms [hr_nid] => 479495 [title] => Small Language Models (SLMs): Applications and Innovations [requirements] => [overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeño en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeños en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 14 [status] => published [changed] => 1715280132 [source_title] => Small Language Models (SLMs): Applications and Innovations [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => slms [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => slms [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => slmsdsa [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => slmsdsa [hr_nid] => 479651 [title] => Small Language Models (SLMs) for Domain-Specific Applications [requirements] =>

Audience

[overview] =>

Small Language Models (SLMs) are a cutting-edge subset of AI that enables efficient language processing on devices with limited computational resources.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data scientists and machine learning engineers who wish to create and apply small language models tailored for specific domains such as legal, medical, and technical fields.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level data scientists and machine learning engineers who wish to create and apply small language models tailored for specific domains such as legal, medical, and technical fields.

By the end of this training, participants will be able to:

[outline] =>

Introduction to Domain-Specific Language Models

Data Curation and Preprocessing

Model Training and Fine-Tuning

Evaluation Metrics and Model Performance

Deployment Strategies

Legal Domain Focus

Medical Domain Focus

Technical Domain Focus

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 28 [status] => published [changed] => 1715281386 [source_title] => Small Language Models (SLMs) for Domain-Specific Applications [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => slmsdsa [hr_nid] => 479651 [title] => Small Language Models (SLMs) for Domain-Specific Applications [requirements] => [overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 28 [status] => published [changed] => 1715281386 [source_title] => Small Language Models (SLMs) for Domain-Specific Applications [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => 1 ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => slmsdsa [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => slmsdsa [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => slmseeai [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => slmseeai [hr_nid] => 479667 [title] => Small Language Models (SLMs): Developing Energy-Efficient AI [requirements] =>

Audience

[overview] =>

Small Language Models (SLMs) are efficient alternatives to larger models, offering comparable performance with significantly reduced computational and energy requirements.

This instructor-led, live training (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to develop energy-efficient AI solutions with small language models that are both powerful and environmentally friendly.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to develop energy-efficient AI solutions with small language models that are both powerful and environmentally friendly.

By the end of this training, participants will be able to:

[outline] =>

Introduction to Energy-Efficient AI

Compact Model Architectures

Optimization and Compression Techniques

Hardware Considerations for AI

Green Coding Practices

Renewable Energy and AI

Lifecycle Assessment of AI Systems

Policy and Regulation for Sustainable AI

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715307649 [source_title] => Small Language Models (SLMs): Developing Energy-Efficient AI [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => slmseeai [hr_nid] => 479667 [title] => Small Language Models (SLMs): Developing Energy-Efficient AI [requirements] => [overview] =>

Los modelos de lenguaje pequeños (SLM) son alternativas eficientes a los modelos más grandes, ya que ofrecen un rendimiento comparable con requisitos computacionales y energéticos significativamente reducidos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático e investigadores de IA de nivel avanzado que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático de nivel avanzado e investigadores de IA que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 21 [status] => published [changed] => 1715307649 [source_title] => Small Language Models (SLMs): Developing Energy-Efficient AI [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => 1 ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => slmseeai [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => slmseeai [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => slmshai [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => slmshai [hr_nid] => 479659 [title] => Small Language Models (SLMs) for Human-AI Interactions [requirements] =>

Audience

[overview] =>

Small Language Models (SLMs) are compact yet powerful tools for enabling sophisticated human-AI interactions in various applications, including conversational AI and customer service bots.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data scientists, machine learning and AI researchers who wish to create engaging and efficient AI-powered conversational experiences with small language models.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level data scientists, machine learning and AI researchers who wish to create engaging and efficient AI-powered conversational experiences with small language models.

By the end of this training, participants will be able to:

[outline] =>

Introduction to Conversational AI and Small Language Models (SLMs)

Designing Conversational Flows

Building Customer Service Bots

Training SLMs for Interaction

Evaluating Interaction Quality

Voice-Enabled and Multimodal Interactions

Personalization and Contextual Understanding

Ethical Considerations and Bias Mitigation

Deployment and Scaling

Capstone Project

Final Assessment

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715283400 [source_title] => Small Language Models (SLMs) for Human-AI Interactions [source_language] => en [cert_code] => [weight] => -1003 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => slmshai [hr_nid] => 479659 [title] => Small Language Models (SLMs) for Human-AI Interactions [requirements] => [overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas compactas pero potentes para permitir interacciones sofisticadas entre humanos e IA en diversas aplicaciones, incluida la IA conversacional y los bots de servicio al cliente.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 14 [status] => published [changed] => 1715283400 [source_title] => Small Language Models (SLMs) for Human-AI Interactions [source_language] => en [cert_code] => [weight] => -1003 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => 1 ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => slmshai [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => slmshai [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => slmsodai [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => slmsodai [hr_nid] => 479671 [title] => Small Language Models (SLMs) for On-Device AI [requirements] =>

Audience

[overview] =>

Small Language Models (SLMs) are efficient and versatile AI tools that can be implemented on a variety of devices, from smartphones to IoT devices, enabling intelligent on-device applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT professionals who wish to deploy small language models directly onto devices with limited processing capabilities, opening up possibilities for innovative applications in various sectors.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level IT professionals who wish to deploy small language models directly onto devices with limited processing capabilities, opening up possibilities for innovative applications in various sectors.

By the end of this training, participants will be able to:

[outline] =>

Introduction to On-Device AI

Model Optimization for On-Device Deployment

Platform-Specific AI Tools and Frameworks

Real-Time Inference and Edge Computing

Power Management and Battery Life Considerations

Security and Privacy in On-Device AI

User Experience and Interaction Design

Scalability and Maintenance

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715323768 [source_title] => Small Language Models (SLMs) for On-Device AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => hitrait [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => slmsodai [hr_nid] => 479671 [title] => Small Language Models (SLMs) for On-Device AI [requirements] => [overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas de IA eficientes y versátiles que se pueden implementar en una variedad de dispositivos, desde teléfonos inteligentes hasta dispositivos IoT, lo que permite aplicaciones inteligentes en el dispositivo.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar pequeños modelos de lenguaje directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar modelos de lenguaje pequeños directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 21 [status] => published [changed] => 1715323768 [source_title] => Small Language Models (SLMs) for On-Device AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => hitrait [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => slmsodai [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => slmsodai [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => geminiai [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => geminiai [hr_nid] => 476043 [title] => Introduction to Google Gemini AI [requirements] =>

Audience


 

[overview] =>

Google Gemini AI is a cutting-edge large language model that offers advanced AI capabilities, such as natural language understanding, text generation, and semantic search, enabling developers to create more intuitive and responsive AI-driven applications.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to integrate AI functionalities into their applications using Google Gemini AI.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to integrate AI functionalities into their applications using Google Gemini AI.

By the end of this training, participants will be able to:

[outline] =>

Introduction to AI and Google Gemini

Understanding Large Language Models (LLMs)

Getting Started with Google Gemini

Working with Gemini Models

Practical Applications of Gemini AI

Advanced Features and Customization

Project - Building an AI Code Buddy

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1711952394 [source_title] => Introduction to Google Gemini AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => geminiai [hr_nid] => 476043 [title] => Introduction to Google Gemini AI [requirements] => [overview] =>

Google Gemini AI es un modelo de lenguaje grande de vanguardia que ofrece capacidades avanzadas de IA, como la comprensión del lenguaje natural, la generación de texto y la búsqueda semántica, lo que permite a los desarrolladores crear aplicaciones impulsadas por IA más intuitivas y receptivas.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 14 [status] => published [changed] => 1711952394 [source_title] => Introduction to Google Gemini AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => 1 [field_overview_in_category] => ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => geminiai [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => geminiai [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => geminiaiforcontentcreation [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => geminiaiforcontentcreation [hr_nid] => 476187 [title] => Google Gemini AI for Content Creation [requirements] =>

Audience

[overview] =>

Google Gemini AI is a transformative tool for content creators, offering capabilities that streamline the creation process of content for various mediums, such as web content, marketing materials, and multimedia projects.

This instructor-led, live training (online or onsite) is aimed at intermediate-level content creators who wish to utilize Google Gemini AI to enhance their content quality and efficiency.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level content creators who wish to utilize Google Gemini AI to enhance their content quality and efficiency.

By the end of this training, participants will be able to:

[outline] =>

Introduction to AI-Powered Content Creation

Setting Up Google Gemini for Content Projects

Automating Content Generation with Gemini AI

Personalizing Content with Gemini AI

SEO Optimization with Gemini AI

Analyzing Content Performance with Gemini AI

Project - Creating a Content Campaign

Conclusion and Future of AI in Content Creation

[language] => en [duration] => 14 [status] => published [changed] => 1711653905 [source_title] => Google Gemini AI for Content Creation [source_language] => en [cert_code] => [weight] => -1007 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => geminiaiforcontentcreation [hr_nid] => 476187 [title] => Google Gemini AI for Content Creation [requirements] => [overview] =>

Google Gemini AI es una herramienta transformadora para los creadores de contenido, que ofrece capacidades que agilizan el proceso de creación de contenido para diversos medios, como contenido web, materiales de marketing y proyectos multimedia.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 14 [status] => published [changed] => 1711653905 [source_title] => Google Gemini AI for Content Creation [source_language] => en [cert_code] => [weight] => -1007 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => 1 ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => geminiaiforcontentcreation [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => geminiaiforcontentcreation [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => geminiaiforcustomerservice [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => geminiaiforcustomerservice [hr_nid] => 476047 [title] => Google Gemini AI for Transformative Customer Service [requirements] =>

Audience

[overview] =>

Google Gemini AI is a versatile tool designed to revolutionize customer service interactions by leveraging advanced machine learning algorithms. It enhances real-time communication across various platforms such as live chat, email support, and social media engagement. By automating routine tasks and providing actionable insights from customer data, Google Gemini AI significantly improves the overall customer experience and operational efficiency.

This instructor-led, live training (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.

By the end of this training, participants will be able to:

[outline] =>

Introduction to AI in Customer Service

Setting Up Google Gemini for Customer Interactions

Automating Customer Support with Gemini AI

Enhancing Customer Engagement

Analyzing Customer Feedback with Gemini AI

Case Studies and Best Practices

Project - Implementing Gemini AI Chatbot

Conclusion and Future Trends

[language] => en [duration] => 14 [status] => published [changed] => 1711648466 [source_title] => Google Gemini AI for Transformative Customer Service [source_language] => en [cert_code] => [weight] => -1006 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => geminiaiforcustomerservice [hr_nid] => 476047 [title] => Google Gemini AI for Transformative Customer Service [requirements] => [overview] =>

Gemini AI es una herramienta versátil diseñada para revolucionar las interacciones de servicio al cliente al aprovechar algoritmos avanzados de aprendizaje automático para comprender y responder a las consultas de los clientes en tiempo real, automatizar tareas rutinarias y proporcionar información procesable a partir de los datos de los clientes, mejorando así la experiencia general del cliente y la eficiencia operativa.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 14 [status] => published [changed] => 1711648466 [source_title] => Google Gemini AI for Transformative Customer Service [source_language] => en [cert_code] => [weight] => -1006 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => geminiaiforcustomerservice [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => geminiaiforcustomerservice [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => geminiaifordataanalysis [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => geminiaifordataanalysis [hr_nid] => 476191 [title] => Google Gemini AI for Data Analysis [requirements] =>

Audience

[overview] =>

Google Gemini AI is a cutting-edge tool that provides users with natural language and visual interfaces to enhance data exploration, analysis, visualization, and communication.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level data analysts and business professionals who wish to perform complex data analysis tasks more intuitively across various industries using Google Gemini AI.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at beginner-level to intermediate-level data analysts and business professionals who wish to perform complex data analysis tasks more intuitively across various industries using Google Gemini AI.

By the end of this training, participants will be able to:

[outline] =>

Introduction to Google Gemini AI

Connecting Data Sources

Exploring Data with Gemini AI

Data Analysis and Insights

Data Visualization

Communicating Insights

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1711656398 [source_title] => Google Gemini AI for Data Analysis [source_language] => en [cert_code] => [weight] => -1008 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => geminiaifordataanalysis [hr_nid] => 476191 [title] => Google Gemini AI for Data Analysis [requirements] => [overview] =>

Google Gemini AI es una herramienta de vanguardia que proporciona a los usuarios interfaces visuales y de lenguaje natural para mejorar la exploración, el análisis, la visualización y la comunicación de datos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que deseen realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que desean realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 21 [status] => published [changed] => 1711656398 [source_title] => Google Gemini AI for Data Analysis [source_language] => en [cert_code] => [weight] => -1008 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => 1 ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => geminiaifordataanalysis [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => geminiaifordataanalysis [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => generativeaillm [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => generativeaillm [hr_nid] => 463251 [title] => Generative AI with Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

Generative AI is a type of AI that can create original content such as text, images, music, and code. Large language models (LLMs) are powerful neural networks that can process and generate natural language. 

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers who wish to learn how to use generative AI with LLMs for various tasks and domains.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level developers who wish to learn how to use generative AI with LLMs for various tasks and domains.

By the end of this training, participants will be able to:

[outline] =>

Introduction to Generative AI

Transformer Architecture and LLMs

Scaling Laws and Optimization

Training and Fine-Tuning LLMs

Deploying and Using LLMs

Ethics and Future of Generative AI

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1709073362 [source_title] => Generative AI with Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => generativeaillm [hr_nid] => 463251 [title] => Generative AI with Large Language Models (LLMs) [requirements] => [overview] =>

La IA generativa es un tipo de IA que puede crear contenido original como texto, imágenes, música y código. Los modelos de lenguaje grandes (LLM) son potentes redes neuronales que pueden procesar y generar lenguaje natural. 

Esta formación en directo dirigida por un instructor (en línea o presencial) está dirigida a desarrolladores de nivel intermedio que deseen aprender a utilizar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel intermedio que desean aprender a usar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 21 [status] => published [changed] => 1709073362 [source_title] => Generative AI with Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => generativeaillm [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => generativeaillm [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => llamaindex [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => llamaindex [hr_nid] => 476587 [title] => LlamaIndex: Enhancing Contextual AI [requirements] =>

Audience

[overview] =>

LlamaIndex is an open-source data framework designed for applications that use Large Language Models (LLMs) and benefit from context augmentation. It's particularly useful for systems known as Retrieval-Augmented Generation (RAG) systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance the capabilities of AI models, making them more accurate and reliable for various applications.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance the capabilities of AI models, making them more accurate and reliable for various applications.

By the end of this training, participants will be able to:

[outline] =>

Introduction to LlamaIndex and Context Augmentation

Setting Up LlamaIndex

Data Indexing and Access

Integrating LlamaIndex with LLMs

Application Scenarios and Case Studies

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712369760 [source_title] => LlamaIndex: Enhancing Contextual AI [source_language] => en [cert_code] => [weight] => -1009 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => llamaindex [hr_nid] => 476587 [title] => LlamaIndex: Enhancing Contextual AI [requirements] => [overview] =>

LlamaIndex es un marco de datos de código abierto diseñado para aplicaciones que usan Large Language Models (LLMs) y se benefician del aumento de contexto. Es particularmente útil para los sistemas conocidos como sistemas de generación aumentada de recuperación (RAG).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 14 [status] => published [changed] => 1712369760 [source_title] => LlamaIndex: Enhancing Contextual AI [source_language] => en [cert_code] => [weight] => -1009 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => 1 ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => llamaindex [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => llamaindex [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => llamaindexdev [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => llamaindexdev [hr_nid] => 476715 [title] => LlamaIndex: Developing LLM Powered Applications [requirements] =>

Audience

[overview] =>

LlamaIndex is a powerful indexing tool designed to enhance the capabilities of Large Language Models (LLMs) by allowing them to retrieve and utilize custom data sets effectively.

This instructor-led, live training (online or onsite) is aimed at beginner-level to advanced-level developers and data scientists who wish to master LlamaIndex for developing innovative LLM-powered applications.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at beginner-level to advanced-level developers and data scientists who wish to master LlamaIndex for developing innovative LLM-powered applications.

By the end of this training, participants will be able to:

[outline] =>

Introduction to LlamaIndex

LlamaIndex in Action

Advanced LlamaIndex Features

Application Development with LlamaIndex

Deployment and Scaling

Ethical and Practical Considerations

Summary and Next Steps

[language] => en [duration] => 42 [status] => published [changed] => 1712622902 [source_title] => LlamaIndex: Developing LLM Powered Applications [source_language] => en [cert_code] => [weight] => -1010 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => llamaindexdev [hr_nid] => 476715 [title] => LlamaIndex: Developing LLM Powered Applications [requirements] => [overview] =>

LlamaIndex es una poderosa herramienta de indexación diseñada para mejorar las capacidades de Large Language Models (LLMs) al permitirles recuperar y utilizar conjuntos de datos personalizados de manera efectiva.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

[outline] => [language] => es [duration] => 42 [status] => published [changed] => 1712622902 [source_title] => LlamaIndex: Developing LLM Powered Applications [source_language] => en [cert_code] => [weight] => -1010 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => 1 [field_course_outline] => 1 [field_prerequisits] => 1 [field_overview_in_category] => 1 ) ) ) ) ) [3] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 54 [function] => hrquery_get_outline_by_cc_langs [args] => Array ( [0] => llamaindexdev [1] => Array ( [0] => en [1] => es ) ) ) [4] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 63 [function] => _hrquery_get_outline_by_course_code [args] => Array ( [0] => llamaindexdev [1] => Array ( [0] => en [1] => es ) ) ) [5] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 74 [function] => hrquery_get_outline_by_course_code [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) [1] => Array ( [0] => en [1] => es ) ) ) [6] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/outlines.logic.php [line] => 174 [function] => hrquery_get_outlines_by_course_codes [args] => Array ( [0] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) ) [7] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 25 [function] => hrquery_outline_get_related [args] => Array ( [0] => hitrave [1] => firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [9] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [10] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [11] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "es" /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module:66 Array ( [0] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 66 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "es" [2] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [3] => 66 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/np_outline/np_outline.module [line] => 25 [function] => np_outline_title [args] => Array ( [0] => llm [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/common/hrquery/frontend/denorm.logic.php [line] => 46 [function] => np_outline_get_value [args] => Array ( [0] => Array ( [en] => stdClass Object ( [course_code] => llm [hr_nid] => 462191 [title] => Introduction to Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

Large Language Models (LLMs) are deep neural network models that can generate natural language texts based on a given input or context. They are trained on large amounts of text data from various domains and sources, and they can capture the syntactic and semantic patterns of natural language. LLMs have achieved impressive results on various natural language tasks such as text summarization, question answering, text generation, and more.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks.

By the end of this training, participants will be able to:

Format of the Course

Course Customization Options

[category_overview] =>

This instructor-led, live training in <loc> (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks.

By the end of this training, participants will be able to:

[outline] =>

Introduction

Understanding LLMs

Getting Started

Working with LLMs

Text Summarization

Question Answering

Text Generation

Integrating LLMs with Other Frameworks and Platforms

Troubleshooting

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1700095996 [source_title] => Introduction to Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [es] => stdClass Object ( [course_code] => llm [hr_nid] => 462191 [title] => Introduction to Large Language Models (LLMs) [requirements] => [overview] =>

Los modelos de lenguaje grandes (LLM) son modelos de redes neuronales profundas que pueden generar textos en lenguaje natural basados en una entrada o contexto determinado. Están entrenados con grandes cantidades de datos de texto de varios dominios y fuentes, y pueden capturar los patrones sintácticos y semánticos del lenguaje natural. Los LLM han logrado resultados impresionantes en varias tareas de lenguaje natural, como el resumen de textos, la respuesta a preguntas, la generación de textos y más.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

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Audiencia

[overview] =>

Adobe Firefly es un producto y un modelo que utiliza IA generativa para crear imágenes, efectos de texto y paletas de colores a partir de simples indicaciones de texto.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introducción

Creación de imágenes con Adobe Firefly

Creación de efectos de texto y paletas de colores con Adobe Firefly

Generación de contenido seguro para uso comercial

Aplicación de principios éticos al uso de la IA generativa

Resumen y próximos pasos

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Audience

[overview] =>

LangChain es un marco de código abierto diseñado para facilitar el desarrollo de aplicaciones utilizando grandes modelos de lenguaje (LLM).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LangChain

Understanding Large Language Models (LLMs)

LangChain Components and Architecture

Integrating LangChain with LLMs

Building Modular Applications

Practical Exercises with LangChain

Advanced LangChain Features

Best Practices and Patterns

Troubleshooting

Summary and Next Steps

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Audience

[overview] =>

LangChain es un marco de código abierto que simplifica la integración de grandes modelos de lenguaje (LLM) en las aplicaciones.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LangChain

Setting Up the Environment

Core Concepts of LangChain

Working with Large Language Models (LLMs)

Developing with LangChain

Troubleshooting

Conclusion and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712091756 [source_title] => LangChain Fundamentals [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => langchainfun ) [slms] => stdClass Object ( [course_code] => slms [hr_nid] => 479495 [title] => Small Language Models (SLMs): Applications and Innovations [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeño en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeños en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Small Language Models (SLMs)

Technical Foundations

SLMs in Natural Language Processing

Real-world Applications of SLMs

Case Studies

Future Directions

Hands-on Workshops

Capstone Project

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715280132 [source_title] => Small Language Models (SLMs): Applications and Innovations [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slms ) [slmsdsa] => stdClass Object ( [course_code] => slmsdsa [hr_nid] => 479651 [title] => Small Language Models (SLMs) for Domain-Specific Applications [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Domain-Specific Language Models

Data Curation and Preprocessing

Model Training and Fine-Tuning

Evaluation Metrics and Model Performance

Deployment Strategies

Legal Domain Focus

Medical Domain Focus

Technical Domain Focus

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 28 [status] => published [changed] => 1715281386 [source_title] => Small Language Models (SLMs) for Domain-Specific Applications [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmsdsa ) [slmseeai] => stdClass Object ( [course_code] => slmseeai [hr_nid] => 479667 [title] => Small Language Models (SLMs): Developing Energy-Efficient AI [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son alternativas eficientes a los modelos más grandes, ya que ofrecen un rendimiento comparable con requisitos computacionales y energéticos significativamente reducidos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático e investigadores de IA de nivel avanzado que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático de nivel avanzado e investigadores de IA que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Energy-Efficient AI

Compact Model Architectures

Optimization and Compression Techniques

Hardware Considerations for AI

Green Coding Practices

Renewable Energy and AI

Lifecycle Assessment of AI Systems

Policy and Regulation for Sustainable AI

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715307649 [source_title] => Small Language Models (SLMs): Developing Energy-Efficient AI [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmseeai ) [slmshai] => stdClass Object ( [course_code] => slmshai [hr_nid] => 479659 [title] => Small Language Models (SLMs) for Human-AI Interactions [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas compactas pero potentes para permitir interacciones sofisticadas entre humanos e IA en diversas aplicaciones, incluida la IA conversacional y los bots de servicio al cliente.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Conversational AI and Small Language Models (SLMs)

Designing Conversational Flows

Building Customer Service Bots

Training SLMs for Interaction

Evaluating Interaction Quality

Voice-Enabled and Multimodal Interactions

Personalization and Contextual Understanding

Ethical Considerations and Bias Mitigation

Deployment and Scaling

Capstone Project

Final Assessment

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715283400 [source_title] => Small Language Models (SLMs) for Human-AI Interactions [source_language] => en [cert_code] => [weight] => -1003 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmshai ) [slmsodai] => stdClass Object ( [course_code] => slmsodai [hr_nid] => 479671 [title] => Small Language Models (SLMs) for On-Device AI [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas de IA eficientes y versátiles que se pueden implementar en una variedad de dispositivos, desde teléfonos inteligentes hasta dispositivos IoT, lo que permite aplicaciones inteligentes en el dispositivo.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar pequeños modelos de lenguaje directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar modelos de lenguaje pequeños directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to On-Device AI

Model Optimization for On-Device Deployment

Platform-Specific AI Tools and Frameworks

Real-Time Inference and Edge Computing

Power Management and Battery Life Considerations

Security and Privacy in On-Device AI

User Experience and Interaction Design

Scalability and Maintenance

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715323768 [source_title] => Small Language Models (SLMs) for On-Device AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => hitrait [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmsodai ) [geminiai] => stdClass Object ( [course_code] => geminiai [hr_nid] => 476043 [title] => Introduction to Google Gemini AI [requirements] =>

Audience


 

[overview] =>

Google Gemini AI es un modelo de lenguaje grande de vanguardia que ofrece capacidades avanzadas de IA, como la comprensión del lenguaje natural, la generación de texto y la búsqueda semántica, lo que permite a los desarrolladores crear aplicaciones impulsadas por IA más intuitivas y receptivas.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI and Google Gemini

Understanding Large Language Models (LLMs)

Getting Started with Google Gemini

Working with Gemini Models

Practical Applications of Gemini AI

Advanced Features and Customization

Project - Building an AI Code Buddy

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1711952394 [source_title] => Introduction to Google Gemini AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiai ) [geminiaiforcontentcreation] => stdClass Object ( [course_code] => geminiaiforcontentcreation [hr_nid] => 476187 [title] => Google Gemini AI for Content Creation [requirements] =>

Audience

[overview] =>

Google Gemini AI es una herramienta transformadora para los creadores de contenido, que ofrece capacidades que agilizan el proceso de creación de contenido para diversos medios, como contenido web, materiales de marketing y proyectos multimedia.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI-Powered Content Creation

Setting Up Google Gemini for Content Projects

Automating Content Generation with Gemini AI

Personalizing Content with Gemini AI

SEO Optimization with Gemini AI

Analyzing Content Performance with Gemini AI

Project - Creating a Content Campaign

Conclusion and Future of AI in Content Creation

[language] => en [duration] => 14 [status] => published [changed] => 1711653905 [source_title] => Google Gemini AI for Content Creation [source_language] => en [cert_code] => [weight] => -1007 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaiforcontentcreation ) [geminiaiforcustomerservice] => stdClass Object ( [course_code] => geminiaiforcustomerservice [hr_nid] => 476047 [title] => Google Gemini AI for Transformative Customer Service [requirements] =>

Audience

[overview] =>

Gemini AI es una herramienta versátil diseñada para revolucionar las interacciones de servicio al cliente al aprovechar algoritmos avanzados de aprendizaje automático para comprender y responder a las consultas de los clientes en tiempo real, automatizar tareas rutinarias y proporcionar información procesable a partir de los datos de los clientes, mejorando así la experiencia general del cliente y la eficiencia operativa.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI in Customer Service

Setting Up Google Gemini for Customer Interactions

Automating Customer Support with Gemini AI

Enhancing Customer Engagement

Analyzing Customer Feedback with Gemini AI

Case Studies and Best Practices

Project - Implementing Gemini AI Chatbot

Conclusion and Future Trends

[language] => en [duration] => 14 [status] => published [changed] => 1711648466 [source_title] => Google Gemini AI for Transformative Customer Service [source_language] => en [cert_code] => [weight] => -1006 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaiforcustomerservice ) [geminiaifordataanalysis] => stdClass Object ( [course_code] => geminiaifordataanalysis [hr_nid] => 476191 [title] => Google Gemini AI for Data Analysis [requirements] =>

Audience

[overview] =>

Google Gemini AI es una herramienta de vanguardia que proporciona a los usuarios interfaces visuales y de lenguaje natural para mejorar la exploración, el análisis, la visualización y la comunicación de datos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que deseen realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que desean realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Google Gemini AI

Connecting Data Sources

Exploring Data with Gemini AI

Data Analysis and Insights

Data Visualization

Communicating Insights

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1711656398 [source_title] => Google Gemini AI for Data Analysis [source_language] => en [cert_code] => [weight] => -1008 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaifordataanalysis ) [generativeaillm] => stdClass Object ( [course_code] => generativeaillm [hr_nid] => 463251 [title] => Generative AI with Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

La IA generativa es un tipo de IA que puede crear contenido original como texto, imágenes, música y código. Los modelos de lenguaje grandes (LLM) son potentes redes neuronales que pueden procesar y generar lenguaje natural. 

Esta formación en directo dirigida por un instructor (en línea o presencial) está dirigida a desarrolladores de nivel intermedio que deseen aprender a utilizar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel intermedio que desean aprender a usar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Generative AI

Transformer Architecture and LLMs

Scaling Laws and Optimization

Training and Fine-Tuning LLMs

Deploying and Using LLMs

Ethics and Future of Generative AI

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1709073362 [source_title] => Generative AI with Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => generativeaillm ) [llamaindex] => stdClass Object ( [course_code] => llamaindex [hr_nid] => 476587 [title] => LlamaIndex: Enhancing Contextual AI [requirements] =>

Audience

[overview] =>

LlamaIndex es un marco de datos de código abierto diseñado para aplicaciones que usan Large Language Models (LLMs) y se benefician del aumento de contexto. Es particularmente útil para los sistemas conocidos como sistemas de generación aumentada de recuperación (RAG).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LlamaIndex and Context Augmentation

Setting Up LlamaIndex

Data Indexing and Access

Integrating LlamaIndex with LLMs

Application Scenarios and Case Studies

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712369760 [source_title] => LlamaIndex: Enhancing Contextual AI [source_language] => en [cert_code] => [weight] => -1009 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llamaindex ) [llamaindexdev] => stdClass Object ( [course_code] => llamaindexdev [hr_nid] => 476715 [title] => LlamaIndex: Developing LLM Powered Applications [requirements] =>

Audience

[overview] =>

LlamaIndex es una poderosa herramienta de indexación diseñada para mejorar las capacidades de Large Language Models (LLMs) al permitirles recuperar y utilizar conjuntos de datos personalizados de manera efectiva.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LlamaIndex

LlamaIndex in Action

Advanced LlamaIndex Features

Application Development with LlamaIndex

Deployment and Scaling

Ethical and Practical Considerations

Summary and Next Steps

[language] => en [duration] => 42 [status] => published [changed] => 1712622902 [source_title] => LlamaIndex: Developing LLM Powered Applications [source_language] => en [cert_code] => [weight] => -1010 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llamaindexdev ) [llm] => stdClass Object ( [course_code] => llm [hr_nid] => 462191 [title] => Introduction to Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje grandes (LLM) son modelos de redes neuronales profundas que pueden generar textos en lenguaje natural basados en una entrada o contexto determinado. Están entrenados con grandes cantidades de datos de texto de varios dominios y fuentes, y pueden capturar los patrones sintácticos y semánticos del lenguaje natural. Los LLM han logrado resultados impresionantes en varias tareas de lenguaje natural, como el resumen de textos, la respuesta a preguntas, la generación de textos y más.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction

Understanding LLMs

Getting Started

Working with LLMs

Text Summarization

Question Answering

Text Generation

Integrating LLMs with Other Frameworks and Platforms

Troubleshooting

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1700095996 [source_title] => Introduction to Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llm ) ) [codes] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) [4] => Array ( [regions] => Array ( [ve_1805] => Array ( [tid] => ve_1805 [title] => Caracas [sales_area] => ve_venezuela [venues] => Array ( [ve_10638169] => Array ( [vid] => ve_10638169 [title] => Caracas - Centro Lido [vfdc] => 250.00 [prices] => Array ( [1] => Array ( [remote guaranteed] => 3150 [classroom guaranteed] => 3650 [remote guaranteed per delegate] => 3150 [delegates] => 1 [adp] => 750 [classroom guaranteed per delegate] => 3650 ) [2] => Array ( [remote guaranteed] => 3900 [classroom guaranteed] => 4550 [remote guaranteed per delegate] => 1950 [delegates] => 2 [adp] => 750 [classroom guaranteed per delegate] => 2275 ) [3] => Array ( [remote guaranteed] => 4650 [classroom guaranteed] => 5451 [remote guaranteed per delegate] => 1550 [delegates] => 3 [adp] => 750 [classroom guaranteed per delegate] => 1817 ) [4] => Array ( [remote guaranteed] => 5400 [classroom guaranteed] => 6352 [remote guaranteed per delegate] => 1350 [delegates] => 4 [adp] => 750 [classroom guaranteed per delegate] => 1588 ) [5] => Array ( [remote guaranteed] => 6150 [classroom guaranteed] => 7250 [remote guaranteed per delegate] => 1230 [delegates] => 5 [adp] => 750 [classroom guaranteed per delegate] => 1450 ) [6] => Array ( [remote guaranteed] => 6900 [classroom guaranteed] => 8148 [remote guaranteed per delegate] => 1150 [delegates] => 6 [adp] => 750 [classroom guaranteed per delegate] => 1358 ) [7] => Array ( [remote guaranteed] => 7651 [classroom guaranteed] => 9051 [remote guaranteed per delegate] => 1093 [delegates] => 7 [adp] => 750 [classroom guaranteed per delegate] => 1293 ) [8] => Array ( [remote guaranteed] => 8400 [classroom guaranteed] => 9952 [remote guaranteed per delegate] => 1050 [delegates] => 8 [adp] => 750 [classroom guaranteed per delegate] => 1244 ) [9] => Array ( [remote guaranteed] => 9153 [classroom guaranteed] => 10854 [remote guaranteed per delegate] => 1017 [delegates] => 9 [adp] => 750 [classroom guaranteed per delegate] => 1206 ) [10] => Array ( [remote guaranteed] => 9900 [classroom guaranteed] => 11750 [remote guaranteed per delegate] => 990 [delegates] => 10 [adp] => 750 [classroom guaranteed per delegate] => 1175 ) ) ) ) ) ) [remote] => Array ( [1] => Array ( [remote guaranteed] => 3150 [remote guaranteed per delegate] => 3150 [adp] => 750 ) [2] => Array ( [remote guaranteed] => 3900 [remote guaranteed per delegate] => 1950 [adp] => 750 ) [3] => Array ( [remote guaranteed] => 4650 [remote guaranteed per delegate] => 1550 [adp] => 750 ) [4] => Array ( [remote guaranteed] => 5400 [remote guaranteed per delegate] => 1350 [adp] => 750 ) [5] => Array ( [remote guaranteed] => 6150 [remote guaranteed per delegate] => 1230 [adp] => 750 ) [6] => Array ( [remote guaranteed] => 6900 [remote guaranteed per delegate] => 1150 [adp] => 750 ) [7] => Array ( [remote guaranteed] => 7651 [remote guaranteed per delegate] => 1093 [adp] => 750 ) [8] => Array ( [remote guaranteed] => 8400 [remote guaranteed per delegate] => 1050 [adp] => 750 ) [9] => Array ( [remote guaranteed] => 9153 [remote guaranteed per delegate] => 1017 [adp] => 750 ) [10] => Array ( [remote guaranteed] => 9900 [remote guaranteed per delegate] => 990 [adp] => 750 ) ) [currency] => USD ) [5] => Array ( ) [6] => Array ( ) [7] => 0 [8] => 1 [9] => 1 [10] => ) ) [4] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [5] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [6] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [7] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) Adobe Firefly: Generative AI for Creatives Training Course

Programa del Curso

Introducción

  • ¿Qué es la IA generativa y Adobe Firefly?
  • IA generativa frente a otros tipos de IA
  • Descripción general de Adobe Características y arquitectura de Firefly
  • Accessing Adobe Firefly en la aplicación web y en Adobe aplicaciones
  • Uso de Adobe créditos y planes de Firefly

Creación de imágenes con Adobe Firefly

  • Generación de imágenes a partir de descripciones de texto
  • Eliminación o adición de objetos en una imagen
  • Generación de imágenes a partir de elementos 3D
  • Mover objetos a cualquier parte de una imagen

Creación de efectos de texto y paletas de colores con Adobe Firefly

  • Aplicación de estilos o texturas a palabras y frases
  • Generación de variaciones de color de ilustraciones vectoriales
  • Creación de elementos de diseño con Adobe Firefly

Generación de contenido seguro para uso comercial

  • Comprender cómo Adobe Firefly se entrena en contenido público y con licencia
  • Saber cómo Adobe Firefly compensa Adobe a los contribuyentes de acciones
  • Comprobación de la licencia y atribución del contenido generado con Adobe Firefly
  • Evitar infringir los derechos de los demás

Aplicación de principios éticos al uso de la IA generativa

  • Aprender sobre el desarrollo responsable de la IA generativa por parte de Adobe
  • Descubriendo Adobe la etiqueta universal de credenciales de contenido "No entrenar"
  • Explorando las iniciativas de Adobe para la autenticidad y procedencia del contenido
  • Usar la IA generativa para mejorar la creatividad, no para reemplazarla
  • Utilizar la IA generativa para obtener resultados positivos y beneficiosos, evitando el daño o el engaño

Resumen y próximos pasos

Requerimientos

  • Comprensión de la IA generativa y sus aplicaciones
  • Experiencia con Adobe aplicaciones como Photoshop, Illustrator y Express
  • Habilidades básicas de diseño y creatividad

Audiencia

  • Diseñadores
  • Artistas
  • Creadores de contenido
 14 horas

Número de participantes



Precio por participante

Los cursos de formación abiertos requieren más de 5 participantes.

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  • Diseñe e implemente interacciones de IA centradas en el usuario.
  • Desarrollar y entrenar SLM para aplicaciones interactivas.
  • Evalúe y mejore la eficacia de la comunicación entre humanos e IA utilizando las métricas adecuadas.
  • Implemente interfaces conversacionales escalables y éticas impulsadas por IA en escenarios del mundo real.
Leer más...

Small Language Models (SLMs) for On-Device AI

 21 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar modelos de lenguaje pequeños directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

  • Comprenda los desafíos y las soluciones para implementar la IA en hardware compacto.
  • Optimice y comprima los modelos de IA para una implementación eficiente en el dispositivo.
  • Utilice marcos y herramientas de IA modernos para la implementación de modelos en el dispositivo.
  • Diseñe y desarrolle aplicaciones de IA en tiempo real para dispositivos móviles e IoT.
  • Evalúe y garantice la seguridad y privacidad de los sistemas de IA en el dispositivo.
Leer más...

Introduction to Google Gemini AI

 14 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

  • Comprender los fundamentos de los modelos de lenguaje grandes.
  • Configure y use Google Gemini AI para varias tareas de IA.
  • Implemente transformaciones de texto a texto e imagen a texto.
  • Cree aplicaciones básicas impulsadas por IA.
  • Explora las funciones avanzadas y las opciones de personalización en Google Gemini AI.
Leer más...

Google Gemini AI for Content Creation

 14 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

  • Comprender el papel de la IA en la creación de contenidos.
  • Configura y usa Google Gemini AI para generar y optimizar contenido.
  • Aplica transformaciones de texto a texto para producir contenido creativo y original.
  • Implemente estrategias de SEO utilizando información impulsada por IA.
  • Analice el rendimiento del contenido y adapte las estrategias utilizando Gemini AI.
Leer más...

Google Gemini AI for Transformative Customer Service

 14 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

  • Comprender el impacto de la IA en el servicio al cliente.
  • Configura Google Gemini AI para automatizar y personalizar las interacciones con los clientes.
  • Utilice transformaciones de texto a texto e imagen a texto para mejorar la eficiencia del servicio.
  • Desarrolle estrategias impulsadas por IA para el análisis de los comentarios de los clientes en tiempo real.
  • Explora las funciones avanzadas para crear una experiencia de servicio al cliente perfecta.
Leer más...

Google Gemini AI for Data Analysis

 21 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que desean realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

  • Comprenda los fundamentos de Google Gemini AI.
  • Conecte varias fuentes de datos a Gemini AI.
  • Explore los datos mediante consultas en lenguaje natural.
  • Analice patrones de datos y obtenga información.
  • Cree visualizaciones de datos atractivas.
  • Comunique información basada en datos de manera efectiva.
Leer más...

Generative AI with Large Language Models (LLMs)

 21 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a desarrolladores de nivel intermedio que desean aprender a usar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

    Explicar qué es la IA generativa y cómo funciona. Describir la arquitectura del transformador que alimenta los LLM. Utilice leyes de escalado empírico para optimizar los LLM para diferentes tareas y restricciones. Aplique herramientas y métodos de última generación para entrenar, ajustar e implementar LLM. Discutir las oportunidades y los riesgos de la IA generativa para la sociedad y las empresas.
Leer más...

LlamaIndex: Enhancing Contextual AI

 14 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

  • Comprender los principios y componentes de LlamaIndex.
  • Ingesta y estructura de datos para su uso con LLM.
  • Implemente el aumento de contexto para mejorar el rendimiento del modelo de IA.
  • Integre LlamaIndex en los sistemas y flujos de trabajo de IA existentes.
Leer más...

LlamaIndex: Developing LLM Powered Applications

 42 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

  • Instale y configure LlamaIndex para su uso con LLM.
  • Indexe y consulte conjuntos de datos personalizados utilizando LlamaIndex para mejorar la funcionalidad de LLM.
  • Diseñe y desarrolle aplicaciones sofisticadas que utilicen LlamaIndex y LLM.
  • Comprender y aplicar las mejores prácticas para trabajar con LLM y LlamaIndex.
  • Navegue por las consideraciones éticas implicadas en la implementación de aplicaciones con tecnología LLM.
Leer más...

Introduction to Large Language Models (LLMs)

 14 horas

Esta capacitación en vivo dirigida por un instructor en Venezuela (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

    Configure un entorno de desarrollo que incluya un LLM popular. Cree un LLM básico y ajústelo en un conjunto de datos personalizado. Utilice los LLM para diferentes tareas de lenguaje natural, como el resumen de textos, la respuesta a preguntas, la generación de textos, etc. Depura y evalúa los LLM con herramientas como TensorBoard, PyTorch Lightning y Hugging Face Datasets.
Leer más...

Categorías Relacionadas

Image for Generative AI category
Generative AI
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Audiencia

[overview] =>

Adobe Firefly es un producto y un modelo que utiliza IA generativa para crear imágenes, efectos de texto y paletas de colores a partir de simples indicaciones de texto.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introducción

Creación de imágenes con Adobe Firefly

Creación de efectos de texto y paletas de colores con Adobe Firefly

Generación de contenido seguro para uso comercial

Aplicación de principios éticos al uso de la IA generativa

Resumen y próximos pasos

[language] => es [duration] => 14 [status] => published [changed] => 1709063812 [source_title] => Adobe Firefly: Generative AI for Creatives [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [1] => Array ( [0] => stdClass Object ( [tid] => 4879 [alias] => cursos-generative-ai [name] => Generative AI [english_name] => Generative AI [consulting_option] => available ) ) [2] => firefly [3] => Array ( [outlines] => Array ( [langchain] => stdClass Object ( [course_code] => langchain [hr_nid] => 476371 [title] => LangChain: Building AI-Powered Applications [requirements] =>

Audience

[overview] =>

LangChain es un marco de código abierto diseñado para facilitar el desarrollo de aplicaciones utilizando grandes modelos de lenguaje (LLM).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LangChain

Understanding Large Language Models (LLMs)

LangChain Components and Architecture

Integrating LangChain with LLMs

Building Modular Applications

Practical Exercises with LangChain

Advanced LangChain Features

Best Practices and Patterns

Troubleshooting

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712088649 [source_title] => LangChain: Building AI-Powered Applications [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => langchain ) [langchainfun] => stdClass Object ( [course_code] => langchainfun [hr_nid] => 476375 [title] => LangChain Fundamentals [requirements] =>

Audience

[overview] =>

LangChain es un marco de código abierto que simplifica la integración de grandes modelos de lenguaje (LLM) en las aplicaciones.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LangChain

Setting Up the Environment

Core Concepts of LangChain

Working with Large Language Models (LLMs)

Developing with LangChain

Troubleshooting

Conclusion and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712091756 [source_title] => LangChain Fundamentals [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => langchainfun ) [slms] => stdClass Object ( [course_code] => slms [hr_nid] => 479495 [title] => Small Language Models (SLMs): Applications and Innovations [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeño en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeños en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Small Language Models (SLMs)

Technical Foundations

SLMs in Natural Language Processing

Real-world Applications of SLMs

Case Studies

Future Directions

Hands-on Workshops

Capstone Project

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715280132 [source_title] => Small Language Models (SLMs): Applications and Innovations [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slms ) [slmsdsa] => stdClass Object ( [course_code] => slmsdsa [hr_nid] => 479651 [title] => Small Language Models (SLMs) for Domain-Specific Applications [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Domain-Specific Language Models

Data Curation and Preprocessing

Model Training and Fine-Tuning

Evaluation Metrics and Model Performance

Deployment Strategies

Legal Domain Focus

Medical Domain Focus

Technical Domain Focus

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 28 [status] => published [changed] => 1715281386 [source_title] => Small Language Models (SLMs) for Domain-Specific Applications [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmsdsa ) [slmseeai] => stdClass Object ( [course_code] => slmseeai [hr_nid] => 479667 [title] => Small Language Models (SLMs): Developing Energy-Efficient AI [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son alternativas eficientes a los modelos más grandes, ya que ofrecen un rendimiento comparable con requisitos computacionales y energéticos significativamente reducidos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático e investigadores de IA de nivel avanzado que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático de nivel avanzado e investigadores de IA que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Energy-Efficient AI

Compact Model Architectures

Optimization and Compression Techniques

Hardware Considerations for AI

Green Coding Practices

Renewable Energy and AI

Lifecycle Assessment of AI Systems

Policy and Regulation for Sustainable AI

Project and Assessment

Summary and Next Steps

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Audience

[overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas compactas pero potentes para permitir interacciones sofisticadas entre humanos e IA en diversas aplicaciones, incluida la IA conversacional y los bots de servicio al cliente.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Conversational AI and Small Language Models (SLMs)

Designing Conversational Flows

Building Customer Service Bots

Training SLMs for Interaction

Evaluating Interaction Quality

Voice-Enabled and Multimodal Interactions

Personalization and Contextual Understanding

Ethical Considerations and Bias Mitigation

Deployment and Scaling

Capstone Project

Final Assessment

Summary and Next Steps

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Audience

[overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas de IA eficientes y versátiles que se pueden implementar en una variedad de dispositivos, desde teléfonos inteligentes hasta dispositivos IoT, lo que permite aplicaciones inteligentes en el dispositivo.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar pequeños modelos de lenguaje directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar modelos de lenguaje pequeños directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to On-Device AI

Model Optimization for On-Device Deployment

Platform-Specific AI Tools and Frameworks

Real-Time Inference and Edge Computing

Power Management and Battery Life Considerations

Security and Privacy in On-Device AI

User Experience and Interaction Design

Scalability and Maintenance

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715323768 [source_title] => Small Language Models (SLMs) for On-Device AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => hitrait [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmsodai ) [geminiai] => stdClass Object ( [course_code] => geminiai [hr_nid] => 476043 [title] => Introduction to Google Gemini AI [requirements] =>

Audience


 

[overview] =>

Google Gemini AI es un modelo de lenguaje grande de vanguardia que ofrece capacidades avanzadas de IA, como la comprensión del lenguaje natural, la generación de texto y la búsqueda semántica, lo que permite a los desarrolladores crear aplicaciones impulsadas por IA más intuitivas y receptivas.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI and Google Gemini

Understanding Large Language Models (LLMs)

Getting Started with Google Gemini

Working with Gemini Models

Practical Applications of Gemini AI

Advanced Features and Customization

Project - Building an AI Code Buddy

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1711952394 [source_title] => Introduction to Google Gemini AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiai ) [geminiaiforcontentcreation] => stdClass Object ( [course_code] => geminiaiforcontentcreation [hr_nid] => 476187 [title] => Google Gemini AI for Content Creation [requirements] =>

Audience

[overview] =>

Google Gemini AI es una herramienta transformadora para los creadores de contenido, que ofrece capacidades que agilizan el proceso de creación de contenido para diversos medios, como contenido web, materiales de marketing y proyectos multimedia.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI-Powered Content Creation

Setting Up Google Gemini for Content Projects

Automating Content Generation with Gemini AI

Personalizing Content with Gemini AI

SEO Optimization with Gemini AI

Analyzing Content Performance with Gemini AI

Project - Creating a Content Campaign

Conclusion and Future of AI in Content Creation

[language] => en [duration] => 14 [status] => published [changed] => 1711653905 [source_title] => Google Gemini AI for Content Creation [source_language] => en [cert_code] => [weight] => -1007 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaiforcontentcreation ) [geminiaiforcustomerservice] => stdClass Object ( [course_code] => geminiaiforcustomerservice [hr_nid] => 476047 [title] => Google Gemini AI for Transformative Customer Service [requirements] =>

Audience

[overview] =>

Gemini AI es una herramienta versátil diseñada para revolucionar las interacciones de servicio al cliente al aprovechar algoritmos avanzados de aprendizaje automático para comprender y responder a las consultas de los clientes en tiempo real, automatizar tareas rutinarias y proporcionar información procesable a partir de los datos de los clientes, mejorando así la experiencia general del cliente y la eficiencia operativa.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI in Customer Service

Setting Up Google Gemini for Customer Interactions

Automating Customer Support with Gemini AI

Enhancing Customer Engagement

Analyzing Customer Feedback with Gemini AI

Case Studies and Best Practices

Project - Implementing Gemini AI Chatbot

Conclusion and Future Trends

[language] => en [duration] => 14 [status] => published [changed] => 1711648466 [source_title] => Google Gemini AI for Transformative Customer Service [source_language] => en [cert_code] => [weight] => -1006 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaiforcustomerservice ) [geminiaifordataanalysis] => stdClass Object ( [course_code] => geminiaifordataanalysis [hr_nid] => 476191 [title] => Google Gemini AI for Data Analysis [requirements] =>

Audience

[overview] =>

Google Gemini AI es una herramienta de vanguardia que proporciona a los usuarios interfaces visuales y de lenguaje natural para mejorar la exploración, el análisis, la visualización y la comunicación de datos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que deseen realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que desean realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Google Gemini AI

Connecting Data Sources

Exploring Data with Gemini AI

Data Analysis and Insights

Data Visualization

Communicating Insights

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1711656398 [source_title] => Google Gemini AI for Data Analysis [source_language] => en [cert_code] => [weight] => -1008 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaifordataanalysis ) [generativeaillm] => stdClass Object ( [course_code] => generativeaillm [hr_nid] => 463251 [title] => Generative AI with Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

La IA generativa es un tipo de IA que puede crear contenido original como texto, imágenes, música y código. Los modelos de lenguaje grandes (LLM) son potentes redes neuronales que pueden procesar y generar lenguaje natural. 

Esta formación en directo dirigida por un instructor (en línea o presencial) está dirigida a desarrolladores de nivel intermedio que deseen aprender a utilizar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel intermedio que desean aprender a usar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Generative AI

Transformer Architecture and LLMs

Scaling Laws and Optimization

Training and Fine-Tuning LLMs

Deploying and Using LLMs

Ethics and Future of Generative AI

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1709073362 [source_title] => Generative AI with Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => generativeaillm ) [llamaindex] => stdClass Object ( [course_code] => llamaindex [hr_nid] => 476587 [title] => LlamaIndex: Enhancing Contextual AI [requirements] =>

Audience

[overview] =>

LlamaIndex es un marco de datos de código abierto diseñado para aplicaciones que usan Large Language Models (LLMs) y se benefician del aumento de contexto. Es particularmente útil para los sistemas conocidos como sistemas de generación aumentada de recuperación (RAG).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LlamaIndex and Context Augmentation

Setting Up LlamaIndex

Data Indexing and Access

Integrating LlamaIndex with LLMs

Application Scenarios and Case Studies

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712369760 [source_title] => LlamaIndex: Enhancing Contextual AI [source_language] => en [cert_code] => [weight] => -1009 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llamaindex ) [llamaindexdev] => stdClass Object ( [course_code] => llamaindexdev [hr_nid] => 476715 [title] => LlamaIndex: Developing LLM Powered Applications [requirements] =>

Audience

[overview] =>

LlamaIndex es una poderosa herramienta de indexación diseñada para mejorar las capacidades de Large Language Models (LLMs) al permitirles recuperar y utilizar conjuntos de datos personalizados de manera efectiva.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LlamaIndex

LlamaIndex in Action

Advanced LlamaIndex Features

Application Development with LlamaIndex

Deployment and Scaling

Ethical and Practical Considerations

Summary and Next Steps

[language] => en [duration] => 42 [status] => published [changed] => 1712622902 [source_title] => LlamaIndex: Developing LLM Powered Applications [source_language] => en [cert_code] => [weight] => -1010 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llamaindexdev ) [llm] => stdClass Object ( [course_code] => llm [hr_nid] => 462191 [title] => Introduction to Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje grandes (LLM) son modelos de redes neuronales profundas que pueden generar textos en lenguaje natural basados en una entrada o contexto determinado. Están entrenados con grandes cantidades de datos de texto de varios dominios y fuentes, y pueden capturar los patrones sintácticos y semánticos del lenguaje natural. Los LLM han logrado resultados impresionantes en varias tareas de lenguaje natural, como el resumen de textos, la respuesta a preguntas, la generación de textos y más.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction

Understanding LLMs

Getting Started

Working with LLMs

Text Summarization

Question Answering

Text Generation

Integrating LLMs with Other Frameworks and Platforms

Troubleshooting

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1700095996 [source_title] => Introduction to Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llm ) ) [codes] => Array ( [0] => langchain [1] => langchainfun [2] => slms [3] => slmsdsa [4] => slmseeai [5] => slmshai [6] => slmsodai [7] => geminiai [8] => geminiaiforcontentcreation [9] => geminiaiforcustomerservice [10] => geminiaifordataanalysis [11] => generativeaillm [12] => llamaindex [13] => llamaindexdev [14] => llm ) ) [4] => Array ( [regions] => Array ( [ve_1805] => Array ( [tid] => ve_1805 [title] => Caracas [sales_area] => ve_venezuela [venues] => Array ( [ve_10638169] => Array ( [vid] => ve_10638169 [title] => Caracas - Centro Lido [vfdc] => 250.00 [prices] => Array ( [1] => Array ( [remote guaranteed] => 3150 [classroom guaranteed] => 3650 [remote guaranteed per delegate] => 3150 [delegates] => 1 [adp] => 750 [classroom guaranteed per delegate] => 3650 ) [2] => Array ( [remote guaranteed] => 3900 [classroom guaranteed] => 4550 [remote guaranteed per delegate] => 1950 [delegates] => 2 [adp] => 750 [classroom guaranteed per delegate] => 2275 ) [3] => Array ( [remote guaranteed] => 4650 [classroom guaranteed] => 5451 [remote guaranteed per delegate] => 1550 [delegates] => 3 [adp] => 750 [classroom guaranteed per delegate] => 1817 ) [4] => Array ( [remote guaranteed] => 5400 [classroom guaranteed] => 6352 [remote guaranteed per delegate] => 1350 [delegates] => 4 [adp] => 750 [classroom guaranteed per delegate] => 1588 ) [5] => Array ( [remote guaranteed] => 6150 [classroom guaranteed] => 7250 [remote guaranteed per delegate] => 1230 [delegates] => 5 [adp] => 750 [classroom guaranteed per delegate] => 1450 ) [6] => Array ( [remote guaranteed] => 6900 [classroom guaranteed] => 8148 [remote guaranteed per delegate] => 1150 [delegates] => 6 [adp] => 750 [classroom guaranteed per delegate] => 1358 ) [7] => Array ( [remote guaranteed] => 7651 [classroom guaranteed] => 9051 [remote guaranteed per delegate] => 1093 [delegates] => 7 [adp] => 750 [classroom guaranteed per delegate] => 1293 ) [8] => Array ( [remote guaranteed] => 8400 [classroom guaranteed] => 9952 [remote guaranteed per delegate] => 1050 [delegates] => 8 [adp] => 750 [classroom guaranteed per delegate] => 1244 ) [9] => Array ( [remote guaranteed] => 9153 [classroom guaranteed] => 10854 [remote guaranteed per delegate] => 1017 [delegates] => 9 [adp] => 750 [classroom guaranteed per delegate] => 1206 ) [10] => Array ( [remote guaranteed] => 9900 [classroom guaranteed] => 11750 [remote guaranteed per delegate] => 990 [delegates] => 10 [adp] => 750 [classroom guaranteed per delegate] => 1175 ) ) ) ) ) ) [remote] => Array ( [1] => Array ( [remote guaranteed] => 3150 [remote guaranteed per delegate] => 3150 [adp] => 750 ) [2] => Array ( [remote guaranteed] => 3900 [remote guaranteed per delegate] => 1950 [adp] => 750 ) [3] => Array ( [remote guaranteed] => 4650 [remote guaranteed per delegate] => 1550 [adp] => 750 ) [4] => Array ( [remote guaranteed] => 5400 [remote guaranteed per delegate] => 1350 [adp] => 750 ) [5] => Array ( [remote guaranteed] => 6150 [remote guaranteed per delegate] => 1230 [adp] => 750 ) [6] => Array ( [remote guaranteed] => 6900 [remote guaranteed per delegate] => 1150 [adp] => 750 ) [7] => Array ( [remote guaranteed] => 7651 [remote guaranteed per delegate] => 1093 [adp] => 750 ) [8] => Array ( [remote guaranteed] => 8400 [remote guaranteed per delegate] => 1050 [adp] => 750 ) [9] => Array ( [remote guaranteed] => 9153 [remote guaranteed per delegate] => 1017 [adp] => 750 ) [10] => Array ( [remote guaranteed] => 9900 [remote guaranteed per delegate] => 990 [adp] => 750 ) ) [currency] => USD ) [5] => Array ( ) [6] => Array ( ) [7] => 0 [8] => 1 [9] => 1 [10] => ) ) [7] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [8] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [9] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [10] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "devel_domain" /apps/nobleprog-website/includes/functions/new-modules-general-functions.php:82 Array ( [0] => Array ( [file] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [line] => 82 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "devel_domain" [2] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [3] => 82 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/islc7/islc7.module [line] => 99 [function] => variable_get [args] => Array ( [0] => devel_domain [1] => ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/islc7/islc7_block.inc [line] => 34 [function] => islc_get_site_list [args] => Array ( ) ) [3] => Array ( [file] => /apps/nobleprog-website/nptemplates/default.php [line] => 265 [function] => islc7_sites_links_array_v3 [args] => Array ( ) ) [4] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 85 [args] => Array ( [0] => /apps/nobleprog-website/nptemplates/default.php ) [function] => require_once ) [5] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 31 [function] => course_render [args] => Array ( [0] => Array ( [course_code] => firefly [hr_nid] => 472879 [title] => Adobe Firefly: Generative AI for Creatives [requirements] =>

Audiencia

[overview] =>

Adobe Firefly es un producto y un modelo que utiliza IA generativa para crear imágenes, efectos de texto y paletas de colores a partir de simples indicaciones de texto.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introducción

Creación de imágenes con Adobe Firefly

Creación de efectos de texto y paletas de colores con Adobe Firefly

Generación de contenido seguro para uso comercial

Aplicación de principios éticos al uso de la IA generativa

Resumen y próximos pasos

[language] => es [duration] => 14 [status] => published [changed] => 1709063812 [source_title] => Adobe Firefly: Generative AI for Creatives [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [1] => Array ( [0] => stdClass Object ( [tid] => 4879 [alias] => cursos-generative-ai [name] => Generative AI [english_name] => Generative AI [consulting_option] => available ) ) [2] => firefly [3] => Array ( [outlines] => Array ( [langchain] => stdClass Object ( [course_code] => langchain [hr_nid] => 476371 [title] => LangChain: Building AI-Powered Applications [requirements] =>

Audience

[overview] =>

LangChain es un marco de código abierto diseñado para facilitar el desarrollo de aplicaciones utilizando grandes modelos de lenguaje (LLM).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LangChain

Understanding Large Language Models (LLMs)

LangChain Components and Architecture

Integrating LangChain with LLMs

Building Modular Applications

Practical Exercises with LangChain

Advanced LangChain Features

Best Practices and Patterns

Troubleshooting

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712088649 [source_title] => LangChain: Building AI-Powered Applications [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => langchain ) [langchainfun] => stdClass Object ( [course_code] => langchainfun [hr_nid] => 476375 [title] => LangChain Fundamentals [requirements] =>

Audience

[overview] =>

LangChain es un marco de código abierto que simplifica la integración de grandes modelos de lenguaje (LLM) en las aplicaciones.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LangChain

Setting Up the Environment

Core Concepts of LangChain

Working with Large Language Models (LLMs)

Developing with LangChain

Troubleshooting

Conclusion and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712091756 [source_title] => LangChain Fundamentals [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => langchainfun ) [slms] => stdClass Object ( [course_code] => slms [hr_nid] => 479495 [title] => Small Language Models (SLMs): Applications and Innovations [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeño en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeños en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Small Language Models (SLMs)

Technical Foundations

SLMs in Natural Language Processing

Real-world Applications of SLMs

Case Studies

Future Directions

Hands-on Workshops

Capstone Project

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715280132 [source_title] => Small Language Models (SLMs): Applications and Innovations [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slms ) [slmsdsa] => stdClass Object ( [course_code] => slmsdsa [hr_nid] => 479651 [title] => Small Language Models (SLMs) for Domain-Specific Applications [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Domain-Specific Language Models

Data Curation and Preprocessing

Model Training and Fine-Tuning

Evaluation Metrics and Model Performance

Deployment Strategies

Legal Domain Focus

Medical Domain Focus

Technical Domain Focus

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 28 [status] => published [changed] => 1715281386 [source_title] => Small Language Models (SLMs) for Domain-Specific Applications [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmsdsa ) [slmseeai] => stdClass Object ( [course_code] => slmseeai [hr_nid] => 479667 [title] => Small Language Models (SLMs): Developing Energy-Efficient AI [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son alternativas eficientes a los modelos más grandes, ya que ofrecen un rendimiento comparable con requisitos computacionales y energéticos significativamente reducidos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático e investigadores de IA de nivel avanzado que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático de nivel avanzado e investigadores de IA que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Energy-Efficient AI

Compact Model Architectures

Optimization and Compression Techniques

Hardware Considerations for AI

Green Coding Practices

Renewable Energy and AI

Lifecycle Assessment of AI Systems

Policy and Regulation for Sustainable AI

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715307649 [source_title] => Small Language Models (SLMs): Developing Energy-Efficient AI [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmseeai ) [slmshai] => stdClass Object ( [course_code] => slmshai [hr_nid] => 479659 [title] => Small Language Models (SLMs) for Human-AI Interactions [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas compactas pero potentes para permitir interacciones sofisticadas entre humanos e IA en diversas aplicaciones, incluida la IA conversacional y los bots de servicio al cliente.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Conversational AI and Small Language Models (SLMs)

Designing Conversational Flows

Building Customer Service Bots

Training SLMs for Interaction

Evaluating Interaction Quality

Voice-Enabled and Multimodal Interactions

Personalization and Contextual Understanding

Ethical Considerations and Bias Mitigation

Deployment and Scaling

Capstone Project

Final Assessment

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715283400 [source_title] => Small Language Models (SLMs) for Human-AI Interactions [source_language] => en [cert_code] => [weight] => -1003 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmshai ) [slmsodai] => stdClass Object ( [course_code] => slmsodai [hr_nid] => 479671 [title] => Small Language Models (SLMs) for On-Device AI [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas de IA eficientes y versátiles que se pueden implementar en una variedad de dispositivos, desde teléfonos inteligentes hasta dispositivos IoT, lo que permite aplicaciones inteligentes en el dispositivo.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar pequeños modelos de lenguaje directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar modelos de lenguaje pequeños directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to On-Device AI

Model Optimization for On-Device Deployment

Platform-Specific AI Tools and Frameworks

Real-Time Inference and Edge Computing

Power Management and Battery Life Considerations

Security and Privacy in On-Device AI

User Experience and Interaction Design

Scalability and Maintenance

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715323768 [source_title] => Small Language Models (SLMs) for On-Device AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => hitrait [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmsodai ) [geminiai] => stdClass Object ( [course_code] => geminiai [hr_nid] => 476043 [title] => Introduction to Google Gemini AI [requirements] =>

Audience


 

[overview] =>

Google Gemini AI es un modelo de lenguaje grande de vanguardia que ofrece capacidades avanzadas de IA, como la comprensión del lenguaje natural, la generación de texto y la búsqueda semántica, lo que permite a los desarrolladores crear aplicaciones impulsadas por IA más intuitivas y receptivas.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI and Google Gemini

Understanding Large Language Models (LLMs)

Getting Started with Google Gemini

Working with Gemini Models

Practical Applications of Gemini AI

Advanced Features and Customization

Project - Building an AI Code Buddy

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1711952394 [source_title] => Introduction to Google Gemini AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiai ) [geminiaiforcontentcreation] => stdClass Object ( [course_code] => geminiaiforcontentcreation [hr_nid] => 476187 [title] => Google Gemini AI for Content Creation [requirements] =>

Audience

[overview] =>

Google Gemini AI es una herramienta transformadora para los creadores de contenido, que ofrece capacidades que agilizan el proceso de creación de contenido para diversos medios, como contenido web, materiales de marketing y proyectos multimedia.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI-Powered Content Creation

Setting Up Google Gemini for Content Projects

Automating Content Generation with Gemini AI

Personalizing Content with Gemini AI

SEO Optimization with Gemini AI

Analyzing Content Performance with Gemini AI

Project - Creating a Content Campaign

Conclusion and Future of AI in Content Creation

[language] => en [duration] => 14 [status] => published [changed] => 1711653905 [source_title] => Google Gemini AI for Content Creation [source_language] => en [cert_code] => [weight] => -1007 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaiforcontentcreation ) [geminiaiforcustomerservice] => stdClass Object ( [course_code] => geminiaiforcustomerservice [hr_nid] => 476047 [title] => Google Gemini AI for Transformative Customer Service [requirements] =>

Audience

[overview] =>

Gemini AI es una herramienta versátil diseñada para revolucionar las interacciones de servicio al cliente al aprovechar algoritmos avanzados de aprendizaje automático para comprender y responder a las consultas de los clientes en tiempo real, automatizar tareas rutinarias y proporcionar información procesable a partir de los datos de los clientes, mejorando así la experiencia general del cliente y la eficiencia operativa.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI in Customer Service

Setting Up Google Gemini for Customer Interactions

Automating Customer Support with Gemini AI

Enhancing Customer Engagement

Analyzing Customer Feedback with Gemini AI

Case Studies and Best Practices

Project - Implementing Gemini AI Chatbot

Conclusion and Future Trends

[language] => en [duration] => 14 [status] => published [changed] => 1711648466 [source_title] => Google Gemini AI for Transformative Customer Service [source_language] => en [cert_code] => [weight] => -1006 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaiforcustomerservice ) [geminiaifordataanalysis] => stdClass Object ( [course_code] => geminiaifordataanalysis [hr_nid] => 476191 [title] => Google Gemini AI for Data Analysis [requirements] =>

Audience

[overview] =>

Google Gemini AI es una herramienta de vanguardia que proporciona a los usuarios interfaces visuales y de lenguaje natural para mejorar la exploración, el análisis, la visualización y la comunicación de datos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que deseen realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que desean realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Google Gemini AI

Connecting Data Sources

Exploring Data with Gemini AI

Data Analysis and Insights

Data Visualization

Communicating Insights

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1711656398 [source_title] => Google Gemini AI for Data Analysis [source_language] => en [cert_code] => [weight] => -1008 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaifordataanalysis ) [generativeaillm] => stdClass Object ( [course_code] => generativeaillm [hr_nid] => 463251 [title] => Generative AI with Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

La IA generativa es un tipo de IA que puede crear contenido original como texto, imágenes, música y código. Los modelos de lenguaje grandes (LLM) son potentes redes neuronales que pueden procesar y generar lenguaje natural. 

Esta formación en directo dirigida por un instructor (en línea o presencial) está dirigida a desarrolladores de nivel intermedio que deseen aprender a utilizar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel intermedio que desean aprender a usar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Generative AI

Transformer Architecture and LLMs

Scaling Laws and Optimization

Training and Fine-Tuning LLMs

Deploying and Using LLMs

Ethics and Future of Generative AI

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1709073362 [source_title] => Generative AI with Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => generativeaillm ) [llamaindex] => stdClass Object ( [course_code] => llamaindex [hr_nid] => 476587 [title] => LlamaIndex: Enhancing Contextual AI [requirements] =>

Audience

[overview] =>

LlamaIndex es un marco de datos de código abierto diseñado para aplicaciones que usan Large Language Models (LLMs) y se benefician del aumento de contexto. Es particularmente útil para los sistemas conocidos como sistemas de generación aumentada de recuperación (RAG).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LlamaIndex and Context Augmentation

Setting Up LlamaIndex

Data Indexing and Access

Integrating LlamaIndex with LLMs

Application Scenarios and Case Studies

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712369760 [source_title] => LlamaIndex: Enhancing Contextual AI [source_language] => en [cert_code] => [weight] => -1009 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llamaindex ) [llamaindexdev] => stdClass Object ( [course_code] => llamaindexdev [hr_nid] => 476715 [title] => LlamaIndex: Developing LLM Powered Applications [requirements] =>

Audience

[overview] =>

LlamaIndex es una poderosa herramienta de indexación diseñada para mejorar las capacidades de Large Language Models (LLMs) al permitirles recuperar y utilizar conjuntos de datos personalizados de manera efectiva.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LlamaIndex

LlamaIndex in Action

Advanced LlamaIndex Features

Application Development with LlamaIndex

Deployment and Scaling

Ethical and Practical Considerations

Summary and Next Steps

[language] => en [duration] => 42 [status] => published [changed] => 1712622902 [source_title] => LlamaIndex: Developing LLM Powered Applications [source_language] => en [cert_code] => [weight] => -1010 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llamaindexdev ) [llm] => stdClass Object ( [course_code] => llm [hr_nid] => 462191 [title] => Introduction to Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje grandes (LLM) son modelos de redes neuronales profundas que pueden generar textos en lenguaje natural basados en una entrada o contexto determinado. Están entrenados con grandes cantidades de datos de texto de varios dominios y fuentes, y pueden capturar los patrones sintácticos y semánticos del lenguaje natural. Los LLM han logrado resultados impresionantes en varias tareas de lenguaje natural, como el resumen de textos, la respuesta a preguntas, la generación de textos y más.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction

Understanding LLMs

Getting Started

Working with LLMs

Text Summarization

Question Answering

Text Generation

Integrating LLMs with Other Frameworks and Platforms

Troubleshooting

Summary and Next Steps

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[classroom guaranteed] => 3650 [remote guaranteed per delegate] => 3150 [delegates] => 1 [adp] => 750 [classroom guaranteed per delegate] => 3650 ) [2] => Array ( [remote guaranteed] => 3900 [classroom guaranteed] => 4550 [remote guaranteed per delegate] => 1950 [delegates] => 2 [adp] => 750 [classroom guaranteed per delegate] => 2275 ) [3] => Array ( [remote guaranteed] => 4650 [classroom guaranteed] => 5451 [remote guaranteed per delegate] => 1550 [delegates] => 3 [adp] => 750 [classroom guaranteed per delegate] => 1817 ) [4] => Array ( [remote guaranteed] => 5400 [classroom guaranteed] => 6352 [remote guaranteed per delegate] => 1350 [delegates] => 4 [adp] => 750 [classroom guaranteed per delegate] => 1588 ) [5] => Array ( [remote guaranteed] => 6150 [classroom guaranteed] => 7250 [remote guaranteed per delegate] => 1230 [delegates] => 5 [adp] => 750 [classroom guaranteed per delegate] => 1450 ) [6] => Array ( [remote guaranteed] => 6900 [classroom guaranteed] => 8148 [remote guaranteed per delegate] => 1150 [delegates] => 6 [adp] => 750 [classroom guaranteed per delegate] => 1358 ) [7] => Array ( [remote guaranteed] => 7651 [classroom guaranteed] => 9051 [remote guaranteed per delegate] => 1093 [delegates] => 7 [adp] => 750 [classroom guaranteed per delegate] => 1293 ) [8] => Array ( [remote guaranteed] => 8400 [classroom guaranteed] => 9952 [remote guaranteed per delegate] => 1050 [delegates] => 8 [adp] => 750 [classroom guaranteed per delegate] => 1244 ) [9] => Array ( [remote guaranteed] => 9153 [classroom guaranteed] => 10854 [remote guaranteed per delegate] => 1017 [delegates] => 9 [adp] => 750 [classroom guaranteed per delegate] => 1206 ) [10] => Array ( [remote guaranteed] => 9900 [classroom guaranteed] => 11750 [remote guaranteed per delegate] => 990 [delegates] => 10 [adp] => 750 [classroom guaranteed per delegate] => 1175 ) ) ) ) ) ) [remote] => Array ( [1] => Array ( [remote guaranteed] => 3150 [remote guaranteed per delegate] => 3150 [adp] => 750 ) [2] => Array ( [remote guaranteed] => 3900 [remote guaranteed per delegate] => 1950 [adp] => 750 ) [3] => Array ( [remote guaranteed] => 4650 [remote guaranteed per delegate] => 1550 [adp] => 750 ) [4] => Array ( [remote guaranteed] => 5400 [remote guaranteed per delegate] => 1350 [adp] => 750 ) [5] => Array ( [remote guaranteed] => 6150 [remote guaranteed per delegate] => 1230 [adp] => 750 ) [6] => Array ( [remote guaranteed] => 6900 [remote guaranteed per delegate] => 1150 [adp] => 750 ) [7] => Array ( [remote guaranteed] => 7651 [remote guaranteed per delegate] => 1093 [adp] => 750 ) [8] => Array ( [remote guaranteed] => 8400 [remote guaranteed per delegate] => 1050 [adp] => 750 ) [9] => Array ( [remote guaranteed] => 9153 [remote guaranteed per delegate] => 1017 [adp] => 750 ) [10] => Array ( [remote guaranteed] => 9900 [remote guaranteed per delegate] => 990 [adp] => 750 ) ) [currency] => USD ) [5] => Array ( ) [6] => Array ( ) [7] => 0 [8] => 1 [9] => 1 [10] => ) ) [6] => Array ( [file] => /apps/nobleprog-website/core/routes.php [line] => 19 [function] => course_menu_callback [args] => Array ( [0] => /cc/firefly ) ) [7] => Array ( [file] => /apps/nobleprog-website/__index.php [line] => 100 [args] => Array ( [0] => /apps/nobleprog-website/core/routes.php ) [function] => require_once ) [8] => Array ( [file] => /apps/nobleprog-website/_index.php [line] => 26 [args] => Array ( [0] => /apps/nobleprog-website/__index.php ) [function] => include_once ) [9] => Array ( [file] => /apps/hitra7/index.php [line] => 54 [args] => Array ( [0] => /apps/nobleprog-website/_index.php ) [function] => include_once ) ) NP URI: www.nobleprog.com.ve/cc/firefly Undefined array key "nobleprog_site_production_url" /apps/nobleprog-website/includes/functions/new-modules-general-functions.php:82 Array ( [0] => Array ( [file] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [line] => 82 [function] => myErrorHandler [args] => Array ( [0] => 2 [1] => Undefined array key "nobleprog_site_production_url" [2] => /apps/nobleprog-website/includes/functions/new-modules-general-functions.php [3] => 82 ) ) [1] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/islc7/islc7.module [line] => 131 [function] => variable_get [args] => Array ( [0] => nobleprog_site_production_url ) ) [2] => Array ( [file] => /apps/hitra7/drupal7/sites/all/modules/_custom/frontend/islc7/islc7_block.inc [line] => 44 [function] => islc_get_current_site [args] => Array ( ) ) [3] => Array ( [file] => /apps/nobleprog-website/nptemplates/default.php [line] => 265 [function] => islc7_sites_links_array_v3 [args] => Array ( ) ) [4] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 85 [args] => Array ( [0] => /apps/nobleprog-website/nptemplates/default.php ) [function] => require_once ) [5] => Array ( [file] => /apps/nobleprog-website/modules/course/course.php [line] => 31 [function] => course_render [args] => Array ( [0] => Array ( [course_code] => firefly [hr_nid] => 472879 [title] => Adobe Firefly: Generative AI for Creatives [requirements] =>

Audiencia

[overview] =>

Adobe Firefly es un producto y un modelo que utiliza IA generativa para crear imágenes, efectos de texto y paletas de colores a partir de simples indicaciones de texto.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a diseñadores, artistas y creadores de contenido de nivel principiante que deseen usar Adobe Firefly para mejorar su creatividad y productividad.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introducción

Creación de imágenes con Adobe Firefly

Creación de efectos de texto y paletas de colores con Adobe Firefly

Generación de contenido seguro para uso comercial

Aplicación de principios éticos al uso de la IA generativa

Resumen y próximos pasos

[language] => es [duration] => 14 [status] => published [changed] => 1709063812 [source_title] => Adobe Firefly: Generative AI for Creatives [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) ) [1] => Array ( [0] => stdClass Object ( [tid] => 4879 [alias] => cursos-generative-ai [name] => Generative AI [english_name] => Generative AI [consulting_option] => available ) ) [2] => firefly [3] => Array ( [outlines] => Array ( [langchain] => stdClass Object ( [course_code] => langchain [hr_nid] => 476371 [title] => LangChain: Building AI-Powered Applications [requirements] =>

Audience

[overview] =>

LangChain es un marco de código abierto diseñado para facilitar el desarrollo de aplicaciones utilizando grandes modelos de lenguaje (LLM).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel intermedio que deseen crear aplicaciones impulsadas por IA utilizando el marco LangChain.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LangChain

Understanding Large Language Models (LLMs)

LangChain Components and Architecture

Integrating LangChain with LLMs

Building Modular Applications

Practical Exercises with LangChain

Advanced LangChain Features

Best Practices and Patterns

Troubleshooting

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712088649 [source_title] => LangChain: Building AI-Powered Applications [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => langchain ) [langchainfun] => stdClass Object ( [course_code] => langchainfun [hr_nid] => 476375 [title] => LangChain Fundamentals [requirements] =>

Audience

[overview] =>

LangChain es un marco de código abierto que simplifica la integración de grandes modelos de lenguaje (LLM) en las aplicaciones.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores e ingenieros de software de nivel principiante a intermedio que deseen aprender los conceptos básicos y la arquitectura de LangChain y adquirir las habilidades prácticas para crear aplicaciones impulsadas por IA.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LangChain

Setting Up the Environment

Core Concepts of LangChain

Working with Large Language Models (LLMs)

Developing with LangChain

Troubleshooting

Conclusion and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712091756 [source_title] => LangChain Fundamentals [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => langchainfun ) [slms] => stdClass Object ( [course_code] => slms [hr_nid] => 479495 [title] => Small Language Models (SLMs): Applications and Innovations [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeño en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos y desarrolladores de nivel principiante a intermedio que deseen implementar y aprovechar modelos de lenguaje pequeños en diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Small Language Models (SLMs)

Technical Foundations

SLMs in Natural Language Processing

Real-world Applications of SLMs

Case Studies

Future Directions

Hands-on Workshops

Capstone Project

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715280132 [source_title] => Small Language Models (SLMs): Applications and Innovations [source_language] => en [cert_code] => [weight] => -1001 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slms ) [slmsdsa] => stdClass Object ( [course_code] => slmsdsa [hr_nid] => 479651 [title] => Small Language Models (SLMs) for Domain-Specific Applications [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son un subconjunto de IA de vanguardia que permite un procesamiento eficiente del lenguaje en dispositivos con recursos computacionales limitados.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a científicos de datos de nivel intermedio e ingenieros de aprendizaje automático que deseen crear y aplicar pequeños modelos de lenguaje adaptados a dominios específicos, como los campos legal, médico y técnico.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Domain-Specific Language Models

Data Curation and Preprocessing

Model Training and Fine-Tuning

Evaluation Metrics and Model Performance

Deployment Strategies

Legal Domain Focus

Medical Domain Focus

Technical Domain Focus

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 28 [status] => published [changed] => 1715281386 [source_title] => Small Language Models (SLMs) for Domain-Specific Applications [source_language] => en [cert_code] => [weight] => -1002 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmsdsa ) [slmseeai] => stdClass Object ( [course_code] => slmseeai [hr_nid] => 479667 [title] => Small Language Models (SLMs): Developing Energy-Efficient AI [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeños (SLM) son alternativas eficientes a los modelos más grandes, ya que ofrecen un rendimiento comparable con requisitos computacionales y energéticos significativamente reducidos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático e investigadores de IA de nivel avanzado que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a ingenieros de aprendizaje automático de nivel avanzado e investigadores de IA que deseen desarrollar soluciones de IA energéticamente eficientes con modelos de lenguaje pequeños que sean potentes y respetuosos con el medio ambiente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Energy-Efficient AI

Compact Model Architectures

Optimization and Compression Techniques

Hardware Considerations for AI

Green Coding Practices

Renewable Energy and AI

Lifecycle Assessment of AI Systems

Policy and Regulation for Sustainable AI

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715307649 [source_title] => Small Language Models (SLMs): Developing Energy-Efficient AI [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmseeai ) [slmshai] => stdClass Object ( [course_code] => slmshai [hr_nid] => 479659 [title] => Small Language Models (SLMs) for Human-AI Interactions [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas compactas pero potentes para permitir interacciones sofisticadas entre humanos e IA en diversas aplicaciones, incluida la IA conversacional y los bots de servicio al cliente.

Esta capacitación en vivo dirigida por un instructor (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o presencial) está dirigida a científicos de datos de nivel intermedio, aprendizaje automático e investigadores de IA que deseen crear experiencias conversacionales atractivas y eficientes impulsadas por IA con modelos de lenguaje pequeños.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Conversational AI and Small Language Models (SLMs)

Designing Conversational Flows

Building Customer Service Bots

Training SLMs for Interaction

Evaluating Interaction Quality

Voice-Enabled and Multimodal Interactions

Personalization and Contextual Understanding

Ethical Considerations and Bias Mitigation

Deployment and Scaling

Capstone Project

Final Assessment

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1715283400 [source_title] => Small Language Models (SLMs) for Human-AI Interactions [source_language] => en [cert_code] => [weight] => -1003 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmshai ) [slmsodai] => stdClass Object ( [course_code] => slmsodai [hr_nid] => 479671 [title] => Small Language Models (SLMs) for On-Device AI [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje pequeño (SLM) son herramientas de IA eficientes y versátiles que se pueden implementar en una variedad de dispositivos, desde teléfonos inteligentes hasta dispositivos IoT, lo que permite aplicaciones inteligentes en el dispositivo.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar pequeños modelos de lenguaje directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de TI de nivel intermedio que desean implementar modelos de lenguaje pequeños directamente en dispositivos con capacidades de procesamiento limitadas, lo que abre posibilidades para aplicaciones innovadoras en diversos sectores.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to On-Device AI

Model Optimization for On-Device Deployment

Platform-Specific AI Tools and Frameworks

Real-Time Inference and Edge Computing

Power Management and Battery Life Considerations

Security and Privacy in On-Device AI

User Experience and Interaction Design

Scalability and Maintenance

Project and Assessment

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1715323768 [source_title] => Small Language Models (SLMs) for On-Device AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => hitrait [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => slmsodai ) [geminiai] => stdClass Object ( [course_code] => geminiai [hr_nid] => 476043 [title] => Introduction to Google Gemini AI [requirements] =>

Audience


 

[overview] =>

Google Gemini AI es un modelo de lenguaje grande de vanguardia que ofrece capacidades avanzadas de IA, como la comprensión del lenguaje natural, la generación de texto y la búsqueda semántica, lo que permite a los desarrolladores crear aplicaciones impulsadas por IA más intuitivas y receptivas.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen integrar funcionalidades de IA en sus aplicaciones utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI and Google Gemini

Understanding Large Language Models (LLMs)

Getting Started with Google Gemini

Working with Gemini Models

Practical Applications of Gemini AI

Advanced Features and Customization

Project - Building an AI Code Buddy

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1711952394 [source_title] => Introduction to Google Gemini AI [source_language] => en [cert_code] => [weight] => -1005 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiai ) [geminiaiforcontentcreation] => stdClass Object ( [course_code] => geminiaiforcontentcreation [hr_nid] => 476187 [title] => Google Gemini AI for Content Creation [requirements] =>

Audience

[overview] =>

Google Gemini AI es una herramienta transformadora para los creadores de contenido, que ofrece capacidades que agilizan el proceso de creación de contenido para diversos medios, como contenido web, materiales de marketing y proyectos multimedia.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a creadores de contenido de nivel intermedio que deseen utilizar Google Gemini AI para mejorar la calidad y eficiencia de su contenido.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI-Powered Content Creation

Setting Up Google Gemini for Content Projects

Automating Content Generation with Gemini AI

Personalizing Content with Gemini AI

SEO Optimization with Gemini AI

Analyzing Content Performance with Gemini AI

Project - Creating a Content Campaign

Conclusion and Future of AI in Content Creation

[language] => en [duration] => 14 [status] => published [changed] => 1711653905 [source_title] => Google Gemini AI for Content Creation [source_language] => en [cert_code] => [weight] => -1007 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaiforcontentcreation ) [geminiaiforcustomerservice] => stdClass Object ( [course_code] => geminiaiforcustomerservice [hr_nid] => 476047 [title] => Google Gemini AI for Transformative Customer Service [requirements] =>

Audience

[overview] =>

Gemini AI es una herramienta versátil diseñada para revolucionar las interacciones de servicio al cliente al aprovechar algoritmos avanzados de aprendizaje automático para comprender y responder a las consultas de los clientes en tiempo real, automatizar tareas rutinarias y proporcionar información procesable a partir de los datos de los clientes, mejorando así la experiencia general del cliente y la eficiencia operativa.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a profesionales de servicio al cliente de nivel intermedio que deseen implementar Google Gemini AI en sus operaciones de servicio al cliente.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to AI in Customer Service

Setting Up Google Gemini for Customer Interactions

Automating Customer Support with Gemini AI

Enhancing Customer Engagement

Analyzing Customer Feedback with Gemini AI

Case Studies and Best Practices

Project - Implementing Gemini AI Chatbot

Conclusion and Future Trends

[language] => en [duration] => 14 [status] => published [changed] => 1711648466 [source_title] => Google Gemini AI for Transformative Customer Service [source_language] => en [cert_code] => [weight] => -1006 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaiforcustomerservice ) [geminiaifordataanalysis] => stdClass Object ( [course_code] => geminiaifordataanalysis [hr_nid] => 476191 [title] => Google Gemini AI for Data Analysis [requirements] =>

Audience

[overview] =>

Google Gemini AI es una herramienta de vanguardia que proporciona a los usuarios interfaces visuales y de lenguaje natural para mejorar la exploración, el análisis, la visualización y la comunicación de datos.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que deseen realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a analistas de datos de nivel principiante a intermedio y profesionales de negocios que desean realizar tareas complejas de análisis de datos de manera más intuitiva en varias industrias utilizando Google Gemini AI.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Google Gemini AI

Connecting Data Sources

Exploring Data with Gemini AI

Data Analysis and Insights

Data Visualization

Communicating Insights

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1711656398 [source_title] => Google Gemini AI for Data Analysis [source_language] => en [cert_code] => [weight] => -1008 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => geminiaifordataanalysis ) [generativeaillm] => stdClass Object ( [course_code] => generativeaillm [hr_nid] => 463251 [title] => Generative AI with Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

La IA generativa es un tipo de IA que puede crear contenido original como texto, imágenes, música y código. Los modelos de lenguaje grandes (LLM) son potentes redes neuronales que pueden procesar y generar lenguaje natural. 

Esta formación en directo dirigida por un instructor (en línea o presencial) está dirigida a desarrolladores de nivel intermedio que deseen aprender a utilizar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel intermedio que desean aprender a usar la IA generativa con LLM para diversas tareas y dominios.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to Generative AI

Transformer Architecture and LLMs

Scaling Laws and Optimization

Training and Fine-Tuning LLMs

Deploying and Using LLMs

Ethics and Future of Generative AI

Summary and Next Steps

[language] => en [duration] => 21 [status] => published [changed] => 1709073362 [source_title] => Generative AI with Large Language Models (LLMs) [source_language] => en [cert_code] => [weight] => -1004 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => generativeaillm ) [llamaindex] => stdClass Object ( [course_code] => llamaindex [hr_nid] => 476587 [title] => LlamaIndex: Enhancing Contextual AI [requirements] =>

Audience

[overview] =>

LlamaIndex es un marco de datos de código abierto diseñado para aplicaciones que usan Large Language Models (LLMs) y se benefician del aumento de contexto. Es particularmente útil para los sistemas conocidos como sistemas de generación aumentada de recuperación (RAG).

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a investigadores de IA de nivel intermedio, profesionales del aprendizaje automático y científicos de datos que deseen utilizar LlamaIndex para mejorar las capacidades de los modelos de IA, haciéndolos más precisos y confiables para diversas aplicaciones.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LlamaIndex and Context Augmentation

Setting Up LlamaIndex

Data Indexing and Access

Integrating LlamaIndex with LLMs

Application Scenarios and Case Studies

Summary and Next Steps

[language] => en [duration] => 14 [status] => published [changed] => 1712369760 [source_title] => LlamaIndex: Enhancing Contextual AI [source_language] => en [cert_code] => [weight] => -1009 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llamaindex ) [llamaindexdev] => stdClass Object ( [course_code] => llamaindexdev [hr_nid] => 476715 [title] => LlamaIndex: Developing LLM Powered Applications [requirements] =>

Audience

[overview] =>

LlamaIndex es una poderosa herramienta de indexación diseñada para mejorar las capacidades de Large Language Models (LLMs) al permitirles recuperar y utilizar conjuntos de datos personalizados de manera efectiva.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores y científicos de datos de nivel principiante a avanzado que deseen dominar LlamaIndex para desarrollar aplicaciones innovadoras impulsadas por LLM.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction to LlamaIndex

LlamaIndex in Action

Advanced LlamaIndex Features

Application Development with LlamaIndex

Deployment and Scaling

Ethical and Practical Considerations

Summary and Next Steps

[language] => en [duration] => 42 [status] => published [changed] => 1712622902 [source_title] => LlamaIndex: Developing LLM Powered Applications [source_language] => en [cert_code] => [weight] => -1010 [excluded_sites] => [use_mt] => stdClass Object ( [field_overview] => [field_course_outline] => [field_prerequisits] => [field_overview_in_category] => ) [cc] => llamaindexdev ) [llm] => stdClass Object ( [course_code] => llm [hr_nid] => 462191 [title] => Introduction to Large Language Models (LLMs) [requirements] =>

Audience

[overview] =>

Los modelos de lenguaje grandes (LLM) son modelos de redes neuronales profundas que pueden generar textos en lenguaje natural basados en una entrada o contexto determinado. Están entrenados con grandes cantidades de datos de texto de varios dominios y fuentes, y pueden capturar los patrones sintácticos y semánticos del lenguaje natural. Los LLM han logrado resultados impresionantes en varias tareas de lenguaje natural, como el resumen de textos, la respuesta a preguntas, la generación de textos y más.

Esta capacitación en vivo dirigida por un instructor (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

Formato del curso

Opciones de personalización del curso

[category_overview] =>

Esta capacitación en vivo dirigida por un instructor en <loc> (en línea o en el sitio) está dirigida a desarrolladores de nivel principiante a intermedio que deseen utilizar modelos de lenguaje grandes para diversas tareas de lenguaje natural.

Al final de esta capacitación, los participantes serán capaces de:

[outline] =>

Introduction

Understanding LLMs

Getting Started

Working with LLMs

Text Summarization

Question Answering

Text Generation

Integrating LLMs with Other Frameworks and Platforms

Troubleshooting

Summary and Next Steps

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