The class takes place on Mondays at 15:30 on Google Meet (the link is sent out before each class). For class we use Jupyter Notebook, which can be run on Google Colab. The notebooks look best locally (GitHub does not render some things), but should also be fine in Google Colab.
Attendance is not mandatory (and due to the online nature of the course will not be checked). However, doing the tasks in the notebooks is (more on that below).
Your final grade will be based on completing the tasks in the notebooks (50%) and a final project (50%). The final grade percentages are as follows:
- 0-49%: 2
- 50-59%: 3
- 60-69%: 3.5
- 70-79%: 4
- 80-89%: 4.5
- 90-100%: 5
The solved notebooks have to be handed in either via sharing by Google Drive or as a forked private GitHub repo (which you'll need to give me access to; please also send me a link to the solution every time) until the day of the next class at 12:00.
The project will be graded based on compliance with the chosen topic, quality of the code, novelty of the idea, and presentation of the results. Details (along with proposed project topics) are in a separate document.