M 10:10am–11:25am · W 4:10pm–5:25pm · T 7:10pm–8:25pm
3 distinct times across 3 sections.
2 of 3 sections have room
Description
This course is an introduction to probability and statistics for data science. Topics include probability theory, probability distributions, simulations, parameters estima- tion, hypothesis testing, simple regression. Python examples will be used throughout the course for illustrations.
Reviews
Course experience
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Instructor quality
n=3, 2023–2024
Aggregated across every course Dobrin Marchev has taught.
Teaching quality
2.8 / 5
Grading fairness
No signal
Workload
No signal
Difficulty
4.0 / 5 · Hard
Overall sentiment
Positive
Sections3
- M 10:10am–11:25am · HAMILTON HALL HAM 702Full
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
- 64 of 86 seats left
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
- 23 of 86 seats left
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
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Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 0 credits
Reported workload
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