{"id":2465,"date":"2025-04-18T11:38:50","date_gmt":"2025-04-18T09:38:50","guid":{"rendered":"https:\/\/aulaonline.uma.es\/?p=2465"},"modified":"2026-05-26T12:34:13","modified_gmt":"2026-05-26T10:34:13","slug":"deep-learning-y-cuda","status":"publish","type":"post","link":"https:\/\/inntech.uma.es\/aulaonline\/deep-learning-y-cuda\/","title":{"rendered":"Deep Learning y CUDA"},"content":{"rendered":"\t\t
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XIV CERTIFICADO DE EXTENSI\u00d3N UNIVERSITARIA DE DEEP LEARNING Y CUDA<\/h3>\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
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DESCRIPCI\u00d3N: <\/strong>Conocer las t\u00e9cnicas m\u00e1s actuales de aprendizaje profundo y aceleraci\u00f3n en GPU de la mano del Deep Learning Institute de Nvidia y obtener sus dos certificaciones m\u00e1s emblem\u00e1ticas.<\/p>\t\t\t\t\t\t\t<\/div>\r\n\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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DIRECCI\u00d3N: <\/strong>Manuel Ujald\u00f3n Mart\u00ednez<\/p>\t\t\t\t\t\t\t<\/div>\r\n\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\t\tArquitectura de Computadores\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\n\t\t<\/div>\n\n\t<\/div>\n\n\t\n\t\t
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PRECIO: <\/strong>395 \u20ac
CR\u00c9DITOS EUROPEOS TOTALES: <\/strong>5 ECTS
HORAS DE CLASE: <\/strong>50
N\u00daMERO DE PLAZAS:<\/strong> 70<\/p>\t\t\t\t\t\t\t<\/div>\r\n\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\n\t\t\n\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<\/path><\/svg>\t\t\t\t<\/span>\n\t\t\t\t\t\t\n\t\t\t\tINSCRIPCI\u00d3N\t\t\t<\/span>\n\t\t<\/span>\n\t<\/a>\n\n\t\n<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Fecha de realizaci\u00f3n: <\/strong>17\/10\/26 – 14\/11\/26\u00a0
Horario: <\/strong>Las 25 horas de clase se impartir\u00e1n de 9 a 14 horas durante 5 s\u00e1bados consecutivos. En los d\u00edas restantes se desarrollan el resto de actividades no presenciales del curso.<\/p>

Plazo de preinscripci\u00f3n: <\/strong>01\/05\/26 – 16\/10\/26
<\/strong>Plazo de matr\u00edcula: <\/strong>01\/05\/26 – 16\/10\/26<\/p>

Requisitos: <\/strong>No se contempla ning\u00fan requisito de acceso ni experiencia profesional previa. Tan s\u00f3lo se recomienda estar familiarizado con los fundamentos de la programaci\u00f3n b\u00e1sica,
como funciones y variables, y tener conocimientos muy elementales de Python.<\/p>\t\t\t\t\t\t\t<\/div>\r\n\t\t\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<\/div>\n\t\t\t\t<\/div>\n\t\t

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M\u00d3DULO 1. Aceleraci\u00f3n en GPU con CUDA <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/i><\/span>\n\t\t\t<\/i><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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1. Arquitectura de la GPU.
2. Aceleraci\u00f3n con GPUs dotadas de miles de cores.
3. Jerarqu\u00eda de millones de hilos en CUDA.
4. Despliegue, coordinaci\u00f3n y sincronizaci\u00f3n de hilos.
5. Los multiprocesadores y su memoria.
6. Gesti\u00f3n eficiente de la memoria de la GPU.
7. Optimizaciones desde el Visual Profiler.
8. Casos estudio de paralelismo masivo.<\/p>\t\t\t\t\t\t\t<\/div>\r\n\t\t\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<\/div>\n\t\t\t\t\t<\/details>\n\t\t\t\t\t\t

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M\u00d3DULO 2. Implementaci\u00f3n de proyectos de Deep Learning sobre GPUs <\/div><\/span>\n\t\t\t\t\t\t\t\n\t\t\t<\/i><\/span>\n\t\t\t<\/i><\/span>\n\t\t<\/span>\n\n\t\t\t\t\t\t<\/summary>\n\t\t\t\t
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1. Entrenamiento e inferencia de redes neuronales profundas en GPUs. Estado del arte.
2. El big bang en aprendizaje profundo. Tendencias actuales.
3. Arquitecturas de las redes neuronales para aplicaciones de supercomputaci\u00f3n.
4. Redes neuronales convolucionales. Aplicaciones y mejoras.
5. Optimizaciones sobre el conjunto de datos y su despliegue en modelos reales.
6. Aprovechamiento de modelos pre-entrenados. Transferencia del aprendizaje.
7. Arquitecturas para el procesamiento del lenguaje natural.
8. Arquitecturas avanzadas: Autoencoders, aprendizaje de refuerzo y GANs Y TRANSFORMERS.<\/p>\t\t\t\t\t\t\t<\/div>\r\n\t\t\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<\/div>\n\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<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Conocer las t\u00e9cnicas m\u00e1s actuales de aprendizaje profundo y aceleraci\u00f3n en GPU de la mano del Deep Learning Institute de NVIDIA y obtener sus dos certificaciones m\u00e1s emblem\u00e1ticas.<\/p>\n","protected":false},"author":2,"featured_media":3755,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-fullwidth.php","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-2465","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ingenieriaabierto"],"yoast_head":"\nDeep Learning y CUDA - Aula Online UMA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/inntech.uma.es\/aulaonline\/deep-learning-y-cuda\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Deep Learning y CUDA - 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