PSYC 4101 Research Practicum in Human and Artificial Intelligence
This course is a practical introduction to the convergence between psychology, neuroscience, and artificial intelligence. Ideas from psychology and neuroscience have inspired the development of artificial neural networks. Their current instantiations, deep neural networks, are having a profound impact on computer science and society, but also on the study of the brain and cognition. This course starts with a brief introduction to the roots of artificial intelligence in psychology and neuroscience, followed by a brief, accessible introduction to the mathematical foundations of deep neural networks. In the remainder of the course, students will learn to use python and pytorch and will work in groups to implement and train deep neural networks to build models of behavior or of the brain. Prior experience with computer programming is highly recommended; students with no experience in programming are encouraged to meet the instructor before enrolling.
Course overview
- Department
- Psychology and Neuroscience
- School
- MCAS
- Credits
- 3
- Level
- Undergraduate
- Offered
- Annually
Catalog details
Requirements fulfilled
Course evaluations
- Course rating
- 4.21 / 5 · Very Good
- Instructor rating
- 4.54 / 5 · Excellent
- Terms evaluated
- 3
| Term | Instructor | Course overall | Instructor overall | Well organized | Clear learning objectives | Intellectually challenging | Helpful assignments | Applicable beyond course | Attendance necessary | Weekly effort | Responses |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Fall 2024 | Stefano Anzellotti | 4.4 | 4.7 | 4.7 | 4.6 | 4.9 | 5.0 | 4.9 | 5.0 | 1–3 hrs/week | 10 of 11 |
| Fall 2023 | Stefano Anzellotti | — | — | — | — | — | — | — | — | — | 13 of 16 |
| Fall 2022 | Stefano Anzellotti | 3.6 | 4.2 | 4.2 | 4.3 | 4.8 | 4.4 | 4.1 | 4.4 | 1–3 hrs/week | 14 of 16 |