CSE 140: Artif Intelligence
University of California, Santa Cruz
Introduction to the contemporary concepts and techniques of artificial intelligence, including any or all of: machine perception and inference, machine learning, optimization problems, computational methods and models of search, game playing and theorem proving. Emphasis may be on any formal method of perceiving, learning, reasoning, and problem solving which proves to be effective. This includes both symbolic and neural network approaches to artificial intelligence. Issues discussed include symbolic versus nonsymbolic methods, local versus global methods, hierarchical organization and control, and brain modeling versus engineering approaches. Lisp or Prolog may be introduced. Involves one major project or regular programming assignments.
Average GPA: 3.63
Grade distribution records: 1,715 students across 16 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 167 | 9.7% |
| A | 804 | 46.9% |
| A- | 234 | 13.6% |
| B+ | 136 | 7.9% |
| B | 100 | 5.8% |
| B- | 66 | 3.8% |
| C+ | 35 | 2.0% |
| C | 29 | 1.7% |
| C- | 5 | 0.3% |
| D+ | 9 | 0.5% |
| D | 7 | 0.4% |
| D- | 1 | 0.1% |
| F | 15 | 0.9% |
| P | 29 | 1.7% |
| NP | 22 | 1.3% |
| W | 54 | 3.1% |
Based on 1,715 student grade records across 16 terms and 5 professors.
Instructors
- Niloofar Montazeri 594 students, Average GPA 3.86
- Leilani Hendrina Gilpin 449 students, Average GPA 3.89
- Narges Norouzi 367 students, Average GPA 3.02
- Lise Getoor 206 students, Average GPA 3.40
- Razvan V Marinescu 99 students, Average GPA 3.66