Reinforcement Learning

Curso

Reinforcement Learning

Departamento de Ingeniería de Sistemas y Computación
Inicio / Programas / Reinforcement Learning

Reinforcement Learning

This course will be taught in English

 

Fees with academic credits:

*If you are in Colombia $4.024.000 COP

*If you are abroad USD $1118

For enrollment click here

 

Fees without academic credits:

*If you are in Colombia $3.733.000 COP

*If you are abroad USD $1040

For enrollment click here

Schedule: tuesday, wednesday, thursday, friday 12:30-17:15, saturday 8:00-13:45

 

*The schedules and modality (virtual or blended) of the courses are subject to modifications according to the provisions of the National and District Government for the management of COVID 19. The dates and times of the sessions can be consulted at mibanner.uniandes.edu.co

Reinforcement Learning (RL) concerns the design of complete agents interacting with stochastic, incomplete and unknown environments, to learn and

adapt the best possible actions to takes to attain a particular objective. This course takes and in-depth look at the mathematical foundations of RL, as well as its practical implementation and best practices.

Este curso hace parte del portafolio de materias de pregrado y posgrado de la Universidad  abiertas a todo público.

Al participar en este curso podrás vivir la experiencia Uniandina, acceder a contenidos de calidad, tomar  clases con estudiantes regulares, acceder al sistema de bibliotecas de Uniandes y participar en las actividades culturales que esta Universidad te ofrece.

Profesores

Ivana Dusparic

Ivana Dusparic is an Ussher Assistant Professor in Future Cities and the Internet of Things in the School of Computer Science and Statistics at Trinity College Dublin. She works on our ENABLE smart cities research programme. Her research interests lie in the use of Artificial Intelligence (machine learning, intelligent agents and multi-agent systems) to achieve autonomous optimization of large-scale heterogeneous infrastructures, with particular focus on smart cities applications and sustainable urban mobility.

Nicolás Cardozo

Ph.D. in Science, Vrije Universiteit Brussel, Belgium Ph.D. in Engineering, Université catholique de Louvain, Belgium M.Sc Computer Science, Vrije Universiteit Brussel, Belgium B.Sc Systems and Computing Engineering, Universidad de los Andes B.Sc Math, Universidad de los Andes

Condiciones

Eventualmente la Universidad puede verse obligada, por causas de fuerza mayor a cambiar sus profesores o cancelar el programa. En este caso el participante podrá optar por la devolución de su dinero o reinvertirlo en otro curso de Educación Continua que se ofrezca en ese momento, asumiendo la diferencia si la hubiere.

La apertura y desarrollo del programa estará sujeto al número de inscritos. El Departamento/Facultad (Unidad académica que ofrece el curso) de la Universidad de los Andes se reserva el derecho de admisión dependiendo del perfil académico de los aspirantes.