Máster en Artificial Intelligence and Deep Learning

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Título

Máster en Artificial Intelligence and Deep Learning

Código del plan de estudios

17312

Universidades participantes

Universidad de Alcalá

Dirección

Director/a

José Ignacio Olmeda Martos

Contacto

Jose Ignacio Olmeda Martos

Cátedra en Big Data y Analítica Predictiva Bancaria

Escuela Politécnica, Laboratorio NL1

Objetivos formativos

  • The study aims to provide a complete training in the field of the use of the tools of Artificial Intelligence and Deep Learning in Business and Industry. It is intended that the student understands the general problem of automated modeling and the enormous applications that it offers.

  • Specifically the study intends that the student is able to:

  • Know the formal foundations of the tools of Automatic Learning and, in particular, of Deep Learning.

  • Be able to implement the different algorithms in high level languages: (Python, R or others) in order to solve real problems and to understand the difficulties of implementing such algorithms in practice.

  • Propose solutions based on Deep Learning from a broad perspective, considering the ethical and legal aspects and the economic and social implications of the automation of the processes in the businesses.

 

Competencias a adquirir

  • Understand and be able to analyze the tools of Artificial Intelligence that can be used in different contexts such as Medicine, Finance or Transportation.

  • Master the different architectures of Deep Learning, its mathematical foundations and its applicability in the context of various problems such as classification or dynamic prediction.

  • Formally understand concepts such as Learning, Generalization, over-training, regularization, etc. and to understand its impact in the construction of applied systems that solve problems.

  • Master programming of data structures and program flow in high-level languages such as Python.

  • Know in depth and be able to use the different tools and design schemes that allow the vectorization the paralleling of the algorithms.

  • Know the main applications of automatic learning in different areas, such as the granting of consumer credit, the grouping of clients according to their typology, the detection of diseases through radiological analysis or the autonomous guidance of vehicles.

 

Público al que va dirigido

Professionals and students interested in understanding the diverse tools of the Artificial Intelligence and Deep Learning applicable in diverse sectors like Medicine, the Finances or the Transport. The profile of the participants mainly includes students from technical careers but also from economics and law or medical sciences given the general applicability of the tools studied in the Master.

Plan de estudios

Edición

Créditos

60 ECTS

Modalidad de enseñanza

On-line y presencial

Periodo de impartición

Consultar con el contacto

Lugar de impartición

Aulas en Centro de Negocios

  (Madrid)

Horario de impartición

Sábados de 9:00 h a 18 h y online

Plazo

Consultar con el contacto

Lugar

Secretaría de Alumnos de Posgrado y Estudios Propios. Escuela de Posgrado,

  Colegio de León.

  C/ Libreros, 21 - 28801 Alcalá de Henares.

  E-mail: secalum.postgrado@uah.es

  Teléfonos: 91 885 4382/ 4364/ 4351   Fax: 91 885 6879

Requisitos generales de acceso

Requisitos adicionales de acceso

Condición adicional

           Se requiere tener nivel de inglés apropiado para la lectura, estudio y comprensión de

           documentación técnica así como para la realización de trabajos escritos de contenido

           especializado

Documentación adicional:

       -  Currículum vítae

Documentación a presentar

Número de plazas

15

Plazo

Consultar con el contacto

Procedimiento

Importe del estudio

precio por crédito: 98,33 €

   importe preinscripción: 1.200,00  €

este importe no incluye precios por servicios administrativos y seguro de accidentes.

Forma de pago

Pago único

Becas

La convocatoria y adjudicación de las becas correrá a cargo de la dirección académica del

  estudio.  El 10% de los ingresos de este estudio serán destinados a becas.

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