{"id":2670,"date":"2026-09-24T07:07:09","date_gmt":"2026-09-24T07:07:09","guid":{"rendered":"https:\/\/xmaintenance.eu\/?page_id=2670"},"modified":"2026-09-24T14:48:13","modified_gmt":"2026-09-24T14:48:13","slug":"professional_skills","status":"publish","type":"page","link":"https:\/\/xmaintenance.eu\/index.php\/professional_skills\/","title":{"rendered":"professional_skills"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"2670\" class=\"elementor elementor-2670\" data-elementor-post-type=\"page\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-32beaeb elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"32beaeb\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-937c189\" data-id=\"937c189\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-09a1cf5 elementor-widget elementor-widget-image\" data-id=\"09a1cf5\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/xmaintenance.eu\/wp-content\/uploads\/elementor\/thumbs\/Fotolia_122977214_Subscription_Monthly_M-rtv6njxk0xf1vwr90azm5z5oou1v13ho0izu18i4oo.jpg\" title=\"Machine learning and artificial intelligence concept. Robot brain with binary coded gears connection and machine learning text. Abstract Electric circuits background and flare light\" alt=\"Machine learning and artificial intelligence concept. Robot brain with binary coded gears connection and machine learning text. Abstract Electric circuits background and flare light\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-23c9938\" data-id=\"23c9938\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-53b299d elementor-widget elementor-widget-heading\" data-id=\"53b299d\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Professional Skills - Applied PdM<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eb0d14f elementor-widget elementor-widget-heading\" data-id=\"eb0d14f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\"><span style=\"color:#3388f6\">Machine Learning aplicado al Mantenimiento Industrial<\/span> <\/h1>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1206ff4 elementor-widget elementor-widget-heading\" data-id=\"1206ff4\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Un programa para profesionales de mantenimiento que necesitan desarrollar criterio t\u00e9cnico para interpretar, validar y aplicar Machine Learning en mantenimiento predictivo, transformando los datos de planta en decisiones fiables.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d100eeb elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"d100eeb\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1e7f430 elementor-widget elementor-widget-text-editor\" data-id=\"1e7f430\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<div class=\"qMYqUG_convSearchResultHighlightRoot\"><div class=\"\" data-turn-id-container=\"request-6a080bd6-90f8-83eb-bce3-08375fcc6511-27\" data-is-intersecting=\"true\"><div class=\"relative w-full overflow-visible\"><section class=\"text-token-text-primary w-full focus:outline-none has-data-writing-block:pointer-events-none [&amp;:has([data-writing-block])&gt;*]:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]\" dir=\"auto\" data-turn-id=\"request-6a080bd6-90f8-83eb-bce3-08375fcc6511-27\" data-turn-id-container=\"request-6a080bd6-90f8-83eb-bce3-08375fcc6511-27\" data-testid=\"conversation-turn-92\" data-scroll-anchor=\"false\" data-turn=\"assistant\"><div class=\"text-base my-auto mx-auto pb-10 [--thread-content-margin:var(--thread-content-margin-xs,calc(var(--spacing)*4))] @w-sm\/main:[--thread-content-margin:var(--thread-content-margin-sm,calc(var(--spacing)*6))] @w-lg\/main:[--thread-content-margin:var(--thread-content-margin-lg,calc(var(--spacing)*16))] px-(--thread-content-margin)\"><div class=\"[--thread-content-max-width:40rem] @w-lg\/main:[--thread-content-max-width:48rem] mx-auto max-w-(--thread-content-max-width) flex-1 group\/turn-messages focus-visible:outline-hidden relative flex w-full min-w-0 flex-col agent-turn\"><div class=\"flex max-w-full flex-col gap-4 grow\"><div class=\"min-h-8 text-message relative flex w-full flex-col items-end gap-2 text-start break-words whitespace-normal outline-none keyboard-focused:focus-ring [.text-message+&amp;]:mt-1\" dir=\"auto\" tabindex=\"0\" data-message-author-role=\"assistant\" data-message-id=\"a0090a83-1b5e-4f23-aa30-fb59bdb18076\" data-message-model-slug=\"gpt-5-3-mini\" data-turn-start-message=\"true\"><div class=\"flex w-full flex-col gap-1 empty:hidden\"><div class=\"markdown prose dark:prose-invert wrap-break-word w-full light markdown-new-styling\"><p data-start=\"0\" data-end=\"128\">Transforme los datos de su planta en <strong>decisiones de mantenimiento basadas en evidencia<\/strong>. Desarrolle las competencias para interpretar, validar y aplicar <strong>Machine Learning al mantenimiento predictivo<\/strong> en situaciones industriales reales.<\/p><p data-start=\"348\" data-end=\"540\" data-is-last-node=\"\" data-is-only-node=\"\">\u00a0<\/p><\/div><\/div><\/div><\/div><\/div><\/div><\/section><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t<div class=\"elementor-element elementor-element-996d3fc e-flex e-con-boxed e-con e-parent\" data-id=\"996d3fc\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-3f9b883 e-con-full e-flex e-con e-child\" data-id=\"3f9b883\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-be93258 e-con-full e-flex e-con e-child\" data-id=\"be93258\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b055f1f elementor-widget elementor-widget-heading\" data-id=\"b055f1f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Punto de partida<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-faaf680 elementor-widget elementor-widget-text-editor\" data-id=\"faaf680\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p class=\"isSelectedEnd\">Hoy muchas organizaciones est\u00e1n incorporando <strong>Inteligencia Artificial al mantenimiento<\/strong>, pero disponer de modelos predictivos no garantiza, por s\u00ed solo, mejores decisiones.<\/p><p class=\"isSelectedEnd\">Se generan dashboards, alertas y <em>scores de salud<\/em> que parecen \u00fatiles, pero que no siempre son <strong>interpretables, robustos o suficientemente fiables para tomar decisiones en planta<\/strong>.<\/p><p>El verdadero reto aparece cuando hay que distinguir entre un modelo que realmente anticipa fallos y otro que simplemente encuentra patrones en los datos. Por eso, los profesionales de mantenimiento necesitan algo m\u00e1s que algoritmos: necesitan <strong>criterio t\u00e9cnico para interpretar, validar y cuestionar los resultados de la IA<\/strong> antes de convertirlos en decisiones de mantenimiento.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ea7e9fa elementor-widget elementor-widget-heading\" data-id=\"ea7e9fa\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Desarrollar criterio para evaluar la IA en mantenimiento<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8c6399e elementor-widget elementor-widget-text-editor\" data-id=\"8c6399e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p class=\"isSelectedEnd\">Este programa tiene como objetivo desarrollar <strong>criterio t\u00e9cnico en Machine Learning aplicado al mantenimiento industrial<\/strong>, para que el participante pueda comprender, interpretar y evaluar modelos predictivos utilizados en entornos reales de planta.<\/p><p class=\"isSelectedEnd\">A lo largo del programa aprender\u00e1 c\u00f3mo los datos se transforman en <strong>variables predictivas<\/strong>, c\u00f3mo funcionan los principales algoritmos y qu\u00e9 m\u00e9tricas permiten determinar si un modelo es realmente fiable para la toma de decisiones de mantenimiento.<\/p><p>El foco no est\u00e1 en programar modelos complejos, sino en desarrollar la capacidad de <strong>saber cu\u00e1ndo confiar en un modelo, cu\u00e1ndo cuestionarlo y qu\u00e9 alternativa utilizar seg\u00fan el objetivo operativo<\/strong>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dac6eb7 elementor-widget elementor-widget-heading\" data-id=\"dac6eb7\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Contenido del programa<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8c81382 elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"8c81382\" data-element_type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-chevron-circle-right\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M256 8c137 0 248 111 248 248S393 504 256 504 8 393 8 256 119 8 256 8zm113.9 231L234.4 103.5c-9.4-9.4-24.6-9.4-33.9 0l-17 17c-9.4 9.4-9.4 24.6 0 33.9L285.1 256 183.5 357.6c-9.4 9.4-9.4 24.6 0 33.9l17 17c9.4 9.4 24.6 9.4 33.9 0L369.9 273c9.4-9.4 9.4-24.6 0-34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Comprenda la arquitectura completa del Mantenimiento Predictivo (PdM), entendiendo c\u00f3mo se integran los datos, los modelos anal\u00edticos y la toma de decisiones en un sistema industrial basado en Machine Learning, desde la captura de informaci\u00f3n hasta la generaci\u00f3n de acciones de mantenimiento.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-chevron-circle-right\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M256 8c137 0 248 111 248 248S393 504 256 504 8 393 8 256 119 8 256 8zm113.9 231L234.4 103.5c-9.4-9.4-24.6-9.4-33.9 0l-17 17c-9.4 9.4-9.4 24.6 0 33.9L285.1 256 183.5 357.6c-9.4 9.4-9.4 24.6 0 33.9l17 17c9.4 9.4 24.6 9.4 33.9 0L369.9 273c9.4-9.4 9.4-24.6 0-34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Profundice en la fase cr\u00edtica de preparaci\u00f3n de datos, incluyendo depuraci\u00f3n, tratamiento de inconsistencias, calidad de la informaci\u00f3n e ingenier\u00eda de caracter\u00edsticas (Feature Engineering) aplicada espec\u00edficamente a variables de mantenimiento, condici\u00f3n de activos y patrones de fallo.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-chevron-circle-right\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M256 8c137 0 248 111 248 248S393 504 256 504 8 393 8 256 119 8 256 8zm113.9 231L234.4 103.5c-9.4-9.4-24.6-9.4-33.9 0l-17 17c-9.4 9.4-9.4 24.6 0 33.9L285.1 256 183.5 357.6c-9.4 9.4-9.4 24.6 0 33.9l17 17c9.4 9.4 24.6 9.4 33.9 0L369.9 273c9.4-9.4 9.4-24.6 0-34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Analice los algoritmos esenciales de Machine Learning utilizados en la industria, comprendiendo su l\u00f3gica de funcionamiento, sus ventajas y limitaciones, y su aplicaci\u00f3n en problemas reales de predicci\u00f3n de fallos, clasificaci\u00f3n y detecci\u00f3n de anomal\u00edas. En este bloque se trabajar\u00e1 con modelos clave como Regresi\u00f3n Log\u00edstica, \u00c1rboles de Decisi\u00f3n, Random Forest, Gradient Boosting (XGBoost\/LightGBM), K-Nearest Neighbors (KNN) y t\u00e9cnicas de clustering como K-Means para detecci\u00f3n de comportamientos an\u00f3malos en activos industriales.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-chevron-circle-right\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M256 8c137 0 248 111 248 248S393 504 256 504 8 393 8 256 119 8 256 8zm113.9 231L234.4 103.5c-9.4-9.4-24.6-9.4-33.9 0l-17 17c-9.4 9.4-9.4 24.6 0 33.9L285.1 256 183.5 357.6c-9.4 9.4-9.4 24.6 0 33.9l17 17c9.4 9.4 24.6 9.4 33.9 0L369.9 273c9.4-9.4 9.4-24.6 0-34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Trabaje en entornos de simulaci\u00f3n con datos reales de planta, donde podr\u00e1 ejecutar modelos, comparar resultados, ajustar par\u00e1metros b\u00e1sicos y evaluar el comportamiento de diferentes enfoques predictivos bajo escenarios industriales controlados.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-chevron-circle-right\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M256 8c137 0 248 111 248 248S393 504 256 504 8 393 8 256 119 8 256 8zm113.9 231L234.4 103.5c-9.4-9.4-24.6-9.4-33.9 0l-17 17c-9.4 9.4-9.4 24.6 0 33.9L285.1 256 183.5 357.6c-9.4 9.4-9.4 24.6 0 33.9l17 17c9.4 9.4 24.6 9.4 33.9 0L369.9 273c9.4-9.4 9.4-24.6 0-34z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Desarrolle competencias pr\u00e1cticas para interpretar resultados de predicci\u00f3n y convertirlos en decisiones de mantenimiento fiables, definiendo acciones en funci\u00f3n del riesgo, la criticidad del activo y el impacto operativo, con criterios claros de soporte a la toma de decisiones.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-60c3ea9 elementor-widget elementor-widget-heading\" data-id=\"60c3ea9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Laboratorios pr\u00e1cticos incluidos<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cb892ab elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"cb892ab\" data-element_type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-check\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M173.898 439.404l-166.4-166.4c-9.997-9.997-9.997-26.206 0-36.204l36.203-36.204c9.997-9.998 26.207-9.998 36.204 0L192 312.69 432.095 72.596c9.997-9.997 26.207-9.997 36.204 0l36.203 36.204c9.997 9.997 9.997 26.206 0 36.204l-294.4 294.401c-9.998 9.997-26.207 9.997-36.204-.001z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Laboratorio 1. Predicci\u00f3n Temprana de Fallas: Construyendo el Primer Clasificador Predictivo<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3b265a0 elementor-widget elementor-widget-text-editor\" data-id=\"3b265a0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Bomba centr\u00edfuga hidr\u00e1ulica utilizada en sistemas industriales de transporte de fluidos. Genera una probabilidad de falla en tiempo real que permita emitir alertas tempranas al personal de mantenimiento y reducir la ocurrencia de fallos inesperados. Empleamos los siguientes algoritmos: Regresi\u00f3n Log\u00edstica, \u00c1rbol de Decisi\u00f3n, Random Forest y M\u00e1quinas de Vectores de Soporte (SVM).<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ec222cb elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"ec222cb\" data-element_type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-check\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M173.898 439.404l-166.4-166.4c-9.997-9.997-9.997-26.206 0-36.204l36.203-36.204c9.997-9.998 26.207-9.998 36.204 0L192 312.69 432.095 72.596c9.997-9.997 26.207-9.997 36.204 0l36.203 36.204c9.997 9.997 9.997 26.206 0 36.204l-294.4 294.401c-9.998 9.997-26.207 9.997-36.204-.001z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Laboratorio 2. Ingenier\u00eda de Alertas Predictivas: Minimizando Falsas Alarmas y Fallos Perdidos<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d6c08b8 elementor-widget elementor-widget-text-editor\" data-id=\"d6c08b8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Compresor de tornillo industrial utilizado en sistemas de aire comprimido. Los participantes comparan diferentes modelos de clasificaci\u00f3n evaluando m\u00e9tricas como precisi\u00f3n, recall, F1-score y curvas ROC. Adem\u00e1s, analizan c\u00f3mo los errores de predicci\u00f3n afectan los costos y la disponibilidad de los activos. Emplearemos los siguientes algoritmos: Regresi\u00f3n Log\u00edstica, Random Forest, Gradient Boosting y XGBoost.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0e0f77b elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"0e0f77b\" data-element_type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-check\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M173.898 439.404l-166.4-166.4c-9.997-9.997-9.997-26.206 0-36.204l36.203-36.204c9.997-9.998 26.207-9.998 36.204 0L192 312.69 432.095 72.596c9.997-9.997 26.207-9.997 36.204 0l36.203 36.204c9.997 9.997 9.997 26.206 0 36.204l-294.4 294.401c-9.998 9.997-26.207 9.997-36.204-.001z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Laboratorio 3. Pron\u00f3stico de Vida \u00datil Remanente: \u00bfCu\u00e1nto Tiempo le Queda al Activo?<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f22e67f elementor-widget elementor-widget-text-editor\" data-id=\"f22e67f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Rodamientos de un compresor de tornillo sometidos a degradaci\u00f3n progresiva. Estimar la Vida \u00datil Remanente (RUL) del activo para apoyar la planificaci\u00f3n de mantenimiento basada en condici\u00f3n. Algoritmos utilizados: Regresi\u00f3n Lineal, Random Forest Regressor, Gradient Boosting Regressor y XGBoost Regressor<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bce0fb5 elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"bce0fb5\" data-element_type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-check\" viewBox=\"0 0 512 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M173.898 439.404l-166.4-166.4c-9.997-9.997-9.997-26.206 0-36.204l36.203-36.204c9.997-9.998 26.207-9.998 36.204 0L192 312.69 432.095 72.596c9.997-9.997 26.207-9.997 36.204 0l36.203 36.204c9.997 9.997 9.997 26.206 0 36.204l-294.4 294.401c-9.998 9.997-26.207 9.997-36.204-.001z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Laboratorio 4. Vigilancia Inteligente de Activos: Detecci\u00f3n Temprana de Anomal\u00edas<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7b68747 elementor-widget elementor-widget-text-editor\" data-id=\"7b68747\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Intercambiador de calor industrial operando bajo condiciones variables de proceso. Detectar comportamientos anormales en el activo, aun cuando no existan registros hist\u00f3ricos de fallas. Se utilizan los siguientes algoritmos: Isolation Forest, Local Outlier Factor (LOF), One-Class SVM, K-Means<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-07d48de elementor-widget elementor-widget-heading\" data-id=\"07d48de\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Metodolog\u00eda<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dc34879 elementor-widget elementor-widget-text-editor\" data-id=\"dc34879\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"2823\" data-end=\"2952\">El programa se desarrolla en formato <b>intensivo de tres a cuatro d\u00edas<\/b>, disponible en modalidad presencial o en formato online para empresas.<\/p><p data-start=\"2954\" data-end=\"3283\">La formaci\u00f3n se basa en laboratorios pr\u00e1cticos con datos reales de planta preparados espec\u00edficamente para simular situaciones industriales. Cada participante trabaja en su propio entorno digital, ejecutando modelos de Machine Learning y analizando sus resultados como si estuviera en un proyecto real de mantenimiento predictivo.<\/p><p data-start=\"3285\" data-end=\"3532\">Estos laboratorios permiten experimentar directamente con los algoritmos, comparar su comportamiento, interpretar m\u00e9tricas de rendimiento y entender sus l\u00edmites. El objetivo es desarrollar criterio t\u00e9cnico a trav\u00e9s de la pr\u00e1ctica, no de la teor\u00eda.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c7d61ed elementor-widget elementor-widget-heading\" data-id=\"c7d61ed\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Dirigido a:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8f7db37 elementor-widget elementor-widget-text-editor\" data-id=\"8f7db37\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"1589\" data-end=\"1851\">Este programa est\u00e1 dise\u00f1ado para profesionales de mantenimiento, fiabilidad, ingenier\u00eda de mantenimiento, digitalizaci\u00f3n industrial y responsables de proyectos de transformaci\u00f3n digital que participan o participar\u00e1n en iniciativas de mantenimiento predictivo.<\/p><p data-start=\"1853\" data-end=\"2088\">Especialmente indicado para jefes de mantenimiento, ingenieros de planta, especialistas en fiabilidad y l\u00edderes t\u00e9cnicos que necesitan entender y validar resultados de modelos de inteligencia artificial sin ser cient\u00edficos de datos.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4192da2 elementor-widget elementor-widget-heading\" data-id=\"4192da2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Resultados el entrenamiento:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3ec54b7 elementor-widget elementor-widget-text-editor\" data-id=\"3ec54b7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"3570\" data-end=\"3623\">Al finalizar el curso, el participante ser\u00e1 capaz de:<\/p><ul data-start=\"3625\" data-end=\"3963\"><li data-section-id=\"1oetr1j\" data-start=\"3625\" data-end=\"3705\">Interpretar modelos de Machine Learning aplicados a mantenimiento industrial<\/li><li data-section-id=\"18idvkk\" data-start=\"3706\" data-end=\"3765\">Evaluar la calidad y fiabilidad de un modelo predictivo<\/li><li data-section-id=\"1i3mvi\" data-start=\"3766\" data-end=\"3830\">Identificar problemas como overfitting o baja generalizaci\u00f3n<\/li><li data-section-id=\"g37sau\" data-start=\"3831\" data-end=\"3897\">Comparar algoritmos seg\u00fan el tipo de problema de mantenimiento<\/li><li data-section-id=\"fib2d7\" data-start=\"3898\" data-end=\"3963\">Tomar decisiones informadas sobre el uso de modelos en planta<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-65ab248 elementor-widget elementor-widget-heading\" data-id=\"65ab248\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Formadores:<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-19345b6 elementor-widget elementor-widget-text-editor\" data-id=\"19345b6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"111\" data-end=\"528\"><b>Hector Ren\u00e9 Alvarez Laverde<\/b>. Licenciado en Matem\u00e1ticas. Maestr\u00eda en Estad\u00edstica aplicada. Maestr\u00eda en Direcci\u00f3n de Producci\u00f3n.\u00a0Doctor (Ph.D) en Ingenier\u00eda Industrial (Ciencia de datos aplicada a la industria)\u00a0por la Universidad Polit\u00e9cnica de Catalu\u00f1a. Recibi\u00f3 entrenamiento como cient\u00edfico de datos industriales en la empresa\u00a0Fuji Xerox de Jap\u00f3n. Certificado como Seis Sigma nivel Master. Formador experto en RAM 4.0 y RCM. Ha desarrollado proyectos de ciencia de datos en sectores como industria petrolera, sider\u00fargica, alimentaci\u00f3n, bebidas, cosm\u00e9tica, cuidado personal, papel, automotriz, qu\u00edmica y tecnolog\u00eda.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-edf2a34 elementor-widget elementor-widget-text-editor\" data-id=\"edf2a34\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p data-start=\"111\" data-end=\"528\"><b>Humberto Alvarez Laverde. <\/b>Ingeniero Mec\u00e1nico. MBA por el IESE Business School. Formaci\u00f3n avanzada en electr\u00f3nica. Graduado en Direcci\u00f3n Industrial en el Instituto Asia Bunka Kaikan de Tokio. Instructor internacional TPM. Certificado en Gesti\u00f3n de Proyectos de Innovaci\u00f3n Tecnol\u00f3gica por la Universidad de Texas A&amp;M. Formado en tecnolog\u00edas de mantenimiento con la Comisi\u00f3n Internacional de Energ\u00eda de Naciones Unidas. Ex director de formaci\u00f3n de la Asociaci\u00f3n Espa\u00f1ola de Mantenimiento. Dilatada carrera profesional como ingeniero, directivo y consultor industrial.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1315a40 elementor-widget elementor-widget-heading\" data-id=\"1315a40\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Preguntas frecuentes (FAQ)<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-878c79b elementor-widget elementor-widget-n-accordion\" data-id=\"878c79b\" data-element_type=\"widget\" data-settings=\"{&quot;default_state&quot;:&quot;expanded&quot;,&quot;max_items_expended&quot;:&quot;one&quot;,&quot;n_accordion_animation_duration&quot;:{&quot;unit&quot;:&quot;ms&quot;,&quot;size&quot;:400,&quot;sizes&quot;:[]}}\" data-widget_type=\"nested-accordion.default\">\n\t\t\t\t\t\t\t<div class=\"e-n-accordion\" aria-label=\"Accordion. Open links with Enter or Space, close with Escape, and navigate with Arrow Keys\">\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-1420\" class=\"e-n-accordion-item\" open>\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"1\" tabindex=\"0\" aria-expanded=\"true\" aria-controls=\"e-n-accordion-item-1420\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> \u00bfNecesito saber programaci\u00f3n para este curso? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1420\" class=\"elementor-element elementor-element-027da31 e-con-full e-flex e-con e-child\" data-id=\"027da31\" data-element_type=\"container\">\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1420\" class=\"elementor-element elementor-element-3295974 e-con-full e-flex e-con e-child\" data-id=\"3295974\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1420\" class=\"elementor-element elementor-element-a12f5b0 e-con-full e-flex e-con e-child\" data-id=\"a12f5b0\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-966985f elementor-widget elementor-widget-text-editor\" data-id=\"966985f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>No es necesario ser programador. Se introducen los conceptos b\u00e1sicos necesarios para trabajar con herramientas de Machine Learning de forma guiada. El proceso de ense\u00f1anza se realiza a trav\u00e9s de laboratorios con herramientas digitales de ejecuci\u00f3n de algoritmos<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-1421\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"2\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-1421\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> \u00bfEs un curso te\u00f3rico con pesada matem\u00e1tica o programaci\u00f3n? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1421\" class=\"elementor-element elementor-element-9680d7a e-con-full e-flex e-con e-child\" data-id=\"9680d7a\" data-element_type=\"container\">\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1421\" class=\"elementor-element elementor-element-82c55c7 e-con-full e-flex e-con e-child\" data-id=\"82c55c7\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1421\" class=\"elementor-element elementor-element-f1971ab e-con-full e-flex e-con e-child\" data-id=\"f1971ab\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-99002b1 elementor-widget elementor-widget-text-editor\" data-id=\"99002b1\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Es un curso altamente pr\u00e1ctico basado en laboratorios con datos reales de planta y simulaciones de escenarios industriales. Las soluciones que emplearemos son \u00abno-code\u00bb y no emplearemos el tiempo de formaci\u00f3n para estudiar tediosos modelos matem\u00e1ticos. Sin embargo, esto no necesariamente implica perder el rigor cient\u00edfico que respaldan los algoritmos.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-1422\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"3\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-1422\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> \u00bfQu\u00e9 herramientas se utilizan? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1422\" class=\"elementor-element elementor-element-4085fe9 e-con-full e-flex e-con e-child\" data-id=\"4085fe9\" data-element_type=\"container\">\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1422\" class=\"elementor-element elementor-element-ef628b4 e-con-full e-flex e-con e-child\" data-id=\"ef628b4\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1422\" class=\"elementor-element elementor-element-ec2a5ce e-con-full e-flex e-con e-child\" data-id=\"ec2a5ce\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a7eda15 elementor-widget elementor-widget-text-editor\" data-id=\"a7eda15\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Se utilizan entornos de laboratorio de Machine Learning (como Orange Data Mining, Knime u otros entornos guiados) dise\u00f1ados para facilitar el aprendizaje aplicado. Cuadernos Colab de Google y Phyton.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-1423\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"4\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-1423\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> \u00bfEs aplicable a mi industria? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1423\" class=\"elementor-element elementor-element-b86f224 e-flex e-con-boxed e-con e-child\" data-id=\"b86f224\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1423\" class=\"elementor-element elementor-element-244cd76 e-con-full e-flex e-con e-child\" data-id=\"244cd76\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1423\" class=\"elementor-element elementor-element-28f4727 e-con-full e-flex e-con e-child\" data-id=\"28f4727\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-288e3cd elementor-widget elementor-widget-text-editor\" data-id=\"288e3cd\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>S\u00ed. Los conceptos y modelos se trabajan desde una perspectiva transversal aplicable a distintos sectores industriales.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t<details id=\"e-n-accordion-item-1424\" class=\"e-n-accordion-item\" >\n\t\t\t\t<summary class=\"e-n-accordion-item-title\" data-accordion-index=\"5\" tabindex=\"-1\" aria-expanded=\"false\" aria-controls=\"e-n-accordion-item-1424\" >\n\t\t\t\t\t<span class='e-n-accordion-item-title-header'><div class=\"e-n-accordion-item-title-text\"> \u00bfQu\u00e9 diferencia este curso de otros cursos de IA? <\/div><\/span>\n\t\t\t\t\t\t\t<span class='e-n-accordion-item-title-icon'>\n\t\t\t<span class='e-opened' ><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-minus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t\t<span class='e-closed'><svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-plus\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M416 208H272V64c0-17.67-14.33-32-32-32h-32c-17.67 0-32 14.33-32 32v144H32c-17.67 0-32 14.33-32 32v32c0 17.67 14.33 32 32 32h144v144c0 17.67 14.33 32 32 32h32c17.67 0 32-14.33 32-32V304h144c17.67 0 32-14.33 32-32v-32c0-17.67-14.33-32-32-32z\"><\/path><\/svg><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1424\" class=\"elementor-element elementor-element-cea644e e-flex e-con-boxed e-con e-child\" data-id=\"cea644e\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1424\" class=\"elementor-element elementor-element-7b6a798 e-con-full e-flex e-con e-child\" data-id=\"7b6a798\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div role=\"region\" aria-labelledby=\"e-n-accordion-item-1424\" class=\"elementor-element elementor-element-c1cefce e-con-full e-flex e-con e-child\" data-id=\"c1cefce\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-000ec26 elementor-widget elementor-widget-text-editor\" data-id=\"000ec26\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Este curso no se centra en programaci\u00f3n ni teor\u00eda matem\u00e1tica avanzada, sino en desarrollar criterio t\u00e9cnico para tomar decisiones reales de mantenimiento basadas en modelos de Machine Learning.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2c9a31c elementor-widget elementor-widget-heading\" data-id=\"2c9a31c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">\u00bfEst\u00e1 su organizaci\u00f3n preparada para tomar decisiones de mantenimiento basadas en predicciones?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b23ed70 elementor-widget elementor-widget-text-editor\" data-id=\"b23ed70\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Solicite informaci\u00f3n sobre la realizaci\u00f3n de este programa en su empresa. Este programa lo podemos impartir en cinco sesiones de tres horas en formato on line en vivo. Cons\u00faltenos alternativas &#8230;<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0e65c61 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"0e65c61\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/xmaintenance.eu\/index.php\/contactos\/\" target=\"_blank\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Solicita informaci\u00f3n adicional de este programa ..<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6638e15 e-con-full e-flex e-con e-child\" data-id=\"6638e15\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4062622 e-flex e-con-boxed e-con e-parent\" data-id=\"4062622\" data-element_type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-d5013e4 e-con-full e-flex e-con e-child\" data-id=\"d5013e4\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6469765 e-con-full e-flex e-con e-child\" data-id=\"6469765\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b8b68a0 elementor-widget elementor-widget-image\" data-id=\"b8b68a0\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"927\" height=\"161\" src=\"https:\/\/xmaintenance.eu\/wp-content\/uploads\/2026\/09\/dark_logo_22.png\" class=\"attachment-large size-large wp-image-2623\" alt=\"\" srcset=\"https:\/\/xmaintenance.eu\/wp-content\/uploads\/2026\/09\/dark_logo_22.png 927w, https:\/\/xmaintenance.eu\/wp-content\/uploads\/2026\/09\/dark_logo_22-300x52.png 300w, https:\/\/xmaintenance.eu\/wp-content\/uploads\/2026\/09\/dark_logo_22-768x133.png 768w\" sizes=\"(max-width: 927px) 100vw, 927px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-42d7306 elementor-widget elementor-widget-text-editor\" data-id=\"42d7306\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>Divisi\u00f3n tecnol\u00f3gica de Apsoluti Business S.L., una organizaci\u00f3n innovadora en procesos de mejora, transformaci\u00f3n industria y desarrollo de equipos altamente cualificados.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-87c8463 e-con-full e-flex e-con e-child\" data-id=\"87c8463\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-fdc2904 e-con-full e-flex e-con e-child\" data-id=\"fdc2904\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5a522be elementor-widget elementor-widget-heading\" data-id=\"5a522be\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Oficinas y representantes<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7c1dbb6 elementor-widget elementor-widget-heading\" data-id=\"7c1dbb6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Barcelona, Espa\u00f1a<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-19e4ba1 elementor-widget elementor-widget-heading\" data-id=\"19e4ba1\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Bristol, UK<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d763446 elementor-widget elementor-widget-heading\" data-id=\"d763446\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Bogot\u00e1, Colombia<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cca7443 elementor-widget elementor-widget-heading\" data-id=\"cca7443\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Miami, USA<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-26c5cd0 e-con-full e-flex e-con e-child\" data-id=\"26c5cd0\" data-element_type=\"container\">\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-af025d9 e-con-full e-flex e-con e-child\" data-id=\"af025d9\" data-element_type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-01ddcdc elementor-widget elementor-widget-heading\" data-id=\"01ddcdc\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Contactos<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-838694d elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"838694d\" data-element_type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fab-whatsapp\" viewBox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M380.9 97.1C339 55.1 283.2 32 223.9 32c-122.4 0-222 99.6-222 222 0 39.1 10.2 77.3 29.6 111L0 480l117.7-30.9c32.4 17.7 68.9 27 106.1 27h.1c122.3 0 224.1-99.6 224.1-222 0-59.3-25.2-115-67.1-157zm-157 341.6c-33.2 0-65.7-8.9-94-25.7l-6.7-4-69.8 18.3L72 359.2l-4.4-7c-18.5-29.4-28.2-63.3-28.2-98.2 0-101.7 82.8-184.5 184.6-184.5 49.3 0 95.6 19.2 130.4 54.1 34.8 34.9 56.2 81.2 56.1 130.5 0 101.8-84.9 184.6-186.6 184.6zm101.2-138.2c-5.5-2.8-32.8-16.2-37.9-18-5.1-1.9-8.8-2.8-12.5 2.8-3.7 5.6-14.3 18-17.6 21.8-3.2 3.7-6.5 4.2-12 1.4-32.6-16.3-54-29.1-75.5-66-5.7-9.8 5.7-9.1 16.3-30.3 1.8-3.7.9-6.9-.5-9.7-1.4-2.8-12.5-30.1-17.1-41.2-4.5-10.8-9.1-9.3-12.5-9.5-3.2-.2-6.9-.2-10.6-.2-3.7 0-9.7 1.4-14.8 6.9-5.1 5.6-19.4 19-19.4 46.3 0 27.3 19.9 53.7 22.6 57.4 2.8 3.7 39.1 59.7 94.8 83.8 35.2 15.2 49 16.5 66.6 13.9 10.7-1.6 32.8-13.4 37.4-26.4 4.6-13 4.6-24.1 3.2-26.4-1.3-2.5-5-3.9-10.5-6.6z\"><\/path><\/svg>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">+34 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