Homeworks are an important grading item of the course (30% of the overall course grade!). They allow you to practically apply the knowledge gained from the lecture material as well as let you acquire the skills that are quintessential for a successful data scientist.
Homework grades are distributed across the following three pillars:
- Correctness of code and results (70% of the HW grade)
- Quality of code (15% of the HW grade)
- Quality of textual description (15% of the HW grade)
- Categories for grading quality of code and textual description:
- Unsatisfactory (0)
- Needs major improvements (25)
- Needs improvements (50)
- Great (75)
- Excellent (100)
Note: For each pillar, the awarded grades are always on a scale of 0-100.
- I think one question of the homework can be interpreted in two ways and I didn’t have enough time to ask TA. What can I do?
- If you think that the question can be interpreted in two ways, you can submit the one that you think is more correct and put the other one in comments. The TA will look at the comments as well.