After successful completion of the course, students are able to:
This lecture introduces theoretical foundations and advanced topics in machine learning. We analyse learning algorithms and show provable guarantees, such as (probabilistic) bounds on the predictive performance.
Tentative topics:
A mix of introductory online lectures (recorded and/or live), exercises with formative feedback and some live sessions where the assigments are discussed.
3ects -> 75h20h (re)viewing lectures and lecture materials10h (re)viewing background material 10h exercises20h coursework15h final project
The final grade consists of