Practical Course Development of Media Systems: Reinforcement Learning
Lecturers: Yannick Weiss, Jesse Grootjen, Florian Bemmann
Professor in Charge: Prof. Sven Mayer
Hours per week: 4
ECTS-Credits: 6
Modul: Master P5.0.2 oder P5.0.4: Gruppenpraktikum zu fortgeschrittenen Themen der Informatik I oder Informatik II
After consultation with the examination board, credit for P2, P3 or P6 (advanced topics for Master) also possible
News
- 08.02.2023: This page is still under development, all content may be subject to change.
Contents
We work on solutions for the use of Machine Learning for Media Systems. During the first half we will learn some basics and consolidate it in small exercises using Python and Unity. In the second hald, you should implement your own ideas and present it as a prototype. The ideas will be implemented and presented as a prototype.
Other lectures on the topic
- Human Computer Interaction
- Machine Learning, e.g. Pratical Machine Learning, Intelligent User Interfaces
Schedule
Please note that due to the engaging nature of the group projects, students have to spend more than the allocated time on the development of their prototypes. This is especially true for the group project implementation scheduled during the lecture break.
| Date | Time | Topic |
|---|---|---|
| TBA | 15:00-17:00 | Lecture 1: Introduction & Project Brainstorming |
| TBA | 14:00-16:00 | Lecture 2: 90-sec Paper Presentation |
| TBA | 14:00-16:00 | Lecture 3: TBA |
| TBA | 14:00-16:00 | Lecture 4: Project Ideation & Group Formation |
| TBA | 14:00-16:00 | Lecture 5: TBA |
| TBA | 16:00-18:00 | Lecture 6: TBA |
| TBA | 16:00-18:00 | Lecture 8: TBA |
| TBA | 16:00-18:00 | Lecture 9: TBA |
| TBA | 09:00-17:00 | Work on the projects |
| TBA | 09:00-17:00 | Work on the projects |
| TBA | 09:00-17:00 | Work on the projects |
| TBA | 09:00-17:00 | Work on the projects |
| TBA | 09:00-12:00 | Work on the projects |
| TBA | 12:00-17:00 | Final presentations |
Location
The course takes at Frauenlobstr. 7A.
Application
Interested students can apply for this practical course via Uni2Work .
The applications should include the following information:
- Describe relevant expertise, for example from previous courses, jobs and other projects, if any, that demonstrate your skills.
- If you already have a project idea that you would like to implement in this course, please sketch it out briefly.
