This course is open only for students of the Data Science Master's programme.
Online Access
Please use this WebEx Link to participate in the online lectures (Monday, 10-14h):
https://fu-berlin.webex.com/fu-berlin-en/j.php?MTID=m18ea5fd82e00d7ebd91624c67d78b5f5
Preliminary schedule
| Week | Topic | Lecturer | Assignments |
| 1 (2.11.) | Introduction | Schütte | none |
| 2 (9.11.) | Prediction Methods | Landgraf | none |
| 3 (16.11.) | Prediction Methods | Landgraf | none |
| 4 (23.11.) | Support Vector Machines / Data Cleansing | Bittracher / Quer | Week 4 by Bittracher |
| 5 (30.11.) | Sampling Techniques | Bittracher | Week 5 by Bittracher |
| 6 (7.12.) | Decision Trees | Landgraf | Week 6 by Landgraf |
| 7 (14.12.) | Prediction Methods | Landgraf | Week 7 by Landgraf |
| 8 (4.01.) | Midterm | Landgraf | Week 8 by Landgraf |
| 9 (11.01.) | Neural Networks | Landgraf | Week 9 by Landgraf |
| 10 (18.01.) | Neural Networks | Landgraf | Week 10 by Landgraf |
| 11 (25.01.) | Unsupervised Learning | Landgraf | Week 11 by Landgraf |
| 12 (1.02.) | Probabilistic data analysis | Koltai | Week 12 by Koltai |
| 13 (8.02.) | Experiment Design | Weber | none |
| 14 (15.02.) | Transformers and Attention | Landgraf | Week 14 by Landgraf |
| 15 (22.02.) | Data visualization and graphs | Schütte/Koltai | Week 15 by Schütte/Koltai |
For the lecture by Prof. Landgraf, see this page: https://mycampus.imp.fu-berlin.de/x/wfenEh
Requirements to get active participation
- Lectures: Write weekly reviews.
- Exercise: Pass all mandatory assignments (starting from week 4 (23.11))