CMPSC 111: INT COMPUTAT SCI
University of California, Santa Barbara
Introduction to the numerical algorithms that form the foundations of data science, machine learning, and computational science and engineering. Matri x computation, linear equation systems, eigenvalue and singular value decom positions, numerical optimization. The informed use of mathematical softwar e environments and libraries, such as python/numpy/scipy.
Average GPA: 3.56
Grade distribution records: 1,971 students across 28 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 354 | 18.0% |
| A | 842 | 42.7% |
| A- | 227 | 11.5% |
| B+ | 89 | 4.5% |
| B | 208 | 10.6% |
| B- | 75 | 3.8% |
| C+ | 51 | 2.6% |
| C | 57 | 2.9% |
| C- | 13 | 0.7% |
| D+ | 5 | 0.3% |
| D | 21 | 1.1% |
| D- | 2 | 0.1% |
| F | 27 | 1.4% |
Based on 1,971 student grade records across 28 terms and 5 professors.
Instructors
- Gibou F G 772 students, Average GPA 3.80
- Matni Z A 604 students, Average GPA 3.31
- Gilbert J R 453 students, Average GPA 3.52
- Bochkov D 71 students, Average GPA 3.27
- Larios Carden 71 students, Average GPA 3.70