| Lecturer |
Prof. Dr. Philipp Baumann |
| Content |
- Students form groups and implement a machine learning system for a real-world business case
- Each group submits a written report that describes the applied algorithms and the obtained results
|
| Degree level |
Master |
| Semester |
Fall |
| Language |
English |
| Prerequisites |
- Recommended master courses: Big Data Analytics or Portfolio Optimization
- Recommended bachelor course: Data Visualization and Machine Learning
- Basic Python skills from recommended courses above
- Free online course that covers required Python skills: https://www.coursera.org/learn/python-data-analysis
|
Dates (preliminary) |
- 14.09.2026: Introduction and assignment of machine learning algorithms to groups
- 28.09.2026: Machine learning with Python
- 19.10.2026: Interim code review
- 30.10.2026: Submission deadline for implementation
- 02.11.2026: Presentation of guidelines for written report
- 09.11.2026: Discussion of implementation with lecturer
- 30.11.2026: Submission deadline for written report
|
| Registration |
Please register until September 10 via e-mail to philipp.baumann@unibe.ch; please include an up-to-date sheet of grades from your Bachelor's and Master's studies. |
| Further information |
KSL
ILIAS
Detailed information (as of May 4, 2026) |
| Evaluation results |
Evaluation fall semester 2025
Honored with the ALL Award for outstanding teaching |
