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)
- Needs minor improvements (75)
- Great (100)
Note: For each pillar, the awarded grades are always on a scale of 0-100.