A&O SCI C111
Introduction to Machine Learning for Physical Sciences
Course statistics
- Predicted GPA
- 3.63
- n = 65 · 3 terms · ± 0.062
- A range
- 80%
- of letter grades
- Taken P/NP
- 2%
- 100% of those passed
- D / F / W
- 4.6%
- 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.
- 1021F
- 2623F
- 3024F
Peak 30
Most recent
30
in 24F
3 terms on record
Grade distribution
- A+ 13 · 19.4%
- A 33 · 49.3%
- A- 6 · 9.0%
- B+ 3 · 4.5%
- B 4 · 6.0%
- B- 1 · 1.5%
- C 2 · 3.0%
- D+ 1 · 1.5%
- F 2 · 3.0%
- P 1 · 1.5%
- I 1 · 1.5%
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 |
|---|---|---|---|---|---|
| LOZINSKI, ALEXANDER RICHARD | 3.64 | 3.64 | 55 | 2 | 82% |
| BORTNIK, JACOB | 3.61 | 3.60 | 10 small sample | 1 | 70% |
“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
- 21F 3.60 n=10
- 23F 3.60 n=25
- 24F 3.67 n=30