Course overview#
Welcome to our course Data Science in Python! 👋
This page contains a weekly overview about the topics, slides and materials for the semester.
Note
This overview will be updated as the semester progresses.
For a more detailed semester overview, take a look at the course-schedule.
Week |
Date |
Content |
Slides |
Materials |
|---|---|---|---|---|
1 |
10.10. |
Introduction |
||
2 |
17.10. |
Data analysis |
||
3 |
24.10. |
Data extraction (web scraping) |
- |
|
4 |
31.10. |
Data extraction (Databases & API) |
||
5 |
07.11. |
Text Mining |
- |
|
6 |
14.11. |
Regression I |
||
7 |
21.11. |
Regression II |
||
8 |
28.11. |
ML case study Duke |
- |
|
9 |
05.12. |
ML Case study CA housing |
- |
|
10 |
12.12. |
Classification |
||
11 |
19.12. |
Decision tree and random forest |
||
12 |
09.01. |
Boosted Tree |
- |
|
13 |
16.01. |
Deep learning |
||
14 |
23.01. |
Deep learning II |
- |
Important links:
