Ph.D. Curriculum
| Curriculum for Direct PhD | ||
|---|---|---|
| Course Code | Course Name | Credits |
| AI5000 | Foundations of Machine Learning | 3 |
| AI5030 | Probability and Stochastic Processes | 3 |
| AI5100 | Deep Learning | 3 |
| AI5110 | Linear Algebra and Applications | 3 |
| AI5120 | Topics in Optimization | 3 |
| AI Electives | 9 | |
| Total | 24 | |
- Direct PhD candidates need to complete 24 credits of coursework in 1 year with 15 credits of mandatory (departmental core) courses.
- Electives not in given list can be considered with approval of faculty advisor and DGPC.
| Curriculum for Regular/External PhD | ||
|---|---|---|
| Course Code | Course Name | Credits |
| AI5000 | Foundations of Machine Learning | 3 |
| AI Electives | 9 | |
| Total | 12 | |
- External PhD candidates need to complete 12 credits of coursework in 1 year with 3 credits of mandatory (departmental core) courses.
- Electives not in the given list can be considered with approval of faculty advisor and DPGC.