| 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) |
- 16.09.2024: Introduction and assignment of machine learning algorithms to groups
- 30.09.2024: Machine learning with Python
- 21.10.2024: Interim code review
- 01.11.2024: Submission deadline for implementation
- 04.11.2024: Presentation of guidelines for written report
- 08.11.2024: Discussion of implementation with lecturer
- 02.12.2024: Submission deadline for written report
|
| Registration |
Please register until September 12 via e-mail to philipp.baumann@unibe.ch; please include an up-to-date sheet of grades. |
| Further information |
KSL
ILIAS
Detailed information (as of August 27, 2025) |
| Evaluation results |
Fall semester 2024
Honored with the ALL Award for outstanding teaching |
