Advanced Topics in Machine Learning

Course description

Content
Advanced machine learning including trending advanced topics typically within: PAC-baysian analysis, advanced support vector machines, deep learning, online learning, reinforcement learning.

Prerequisites 
Solid mathematical foundation and knowledge of Machine Learning corresponding to the course Machine Learning above and programming experience.

Practical information

The course is offered as a single-subject course at the Faculty of Science. Single-subject courses typically run for seven to nine weeks with scheduled activities approx. one day per week.

You will be attending the course together with full-time students from the Faculty of Science, and you must meet various admission requirements. The course ends with an exam.

The number of places is limited, and they are allocated on a first-come, first-served basis, so do not delay your application!