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.