COM SCI 188
Special Courses in Computer Science: Introduction to Machine Learning for Computer Scientists
Course statistics
- Predicted GPA
- 3.57
- n = 566 · 5 terms · ± 0.023
- A range
- 66%
- of letter grades
- Taken P/NP
- 0%
- — of those passed
- D / F / W
- 1.2%
- incl. withdrawals
Sections in Fall 2026
Not offered in Fall 2026.
Enrollment history
Final enrollment per term, averaged across that term's sections. Four years deep, summer excluded. Per-section live curves are on each section page.
- 7022W
- 5522F
- 8023W
- 14024W
- 7625S
Peak 140
Most recent
76
in 25S
5 terms on record
Grade distribution
- A+ 117 · 20.7%
- A 153 · 27.0%
- A- 106 · 18.7%
- B+ 84 · 14.8%
- B 44 · 7.8%
- B- 33 · 5.8%
- C+ 14 · 2.5%
- C 4 · 0.7%
- C- 4 · 0.7%
- D 3 · 0.5%
- D- 1 · 0.2%
- F 3 · 0.5%
Grey bars are non-letter outcomes — P/NP, S/U, incompletes. They are excluded from the GPA entirely rather than scored, because counting a P as a 4.0 would be a fabrication.
By instructor
| Instructor | Predicted | Raw | n | Terms | A range |
|---|---|---|---|---|---|
| ZHOU, BOLEI | 3.46 | 3.45 | 256 | 3 | 60% |
| PENG, NANYUN | 3.58 | 3.58 | 158 | 2 | 63% |
| JUN, EUNICE | 3.83 | 3.87 | 79 | 1 | 89% |
| CUI, YUCHEN | 3.63 | 3.64 | 73 | 1 | 74% |
“Predicted” is shrunk toward the course average, which is itself shrunk toward the department — so an instructor with a handful of students sits near the course mean rather than topping the list.
By term
- 22W 3.60 n=139
- 22F 3.67 n=55
- 23W 3.50 n=80
- 24W 3.34 n=140
- 25S 3.76 n=152