Details of CS2102 (Autumn 2026)
| Level: 2 | Type: Theory | Credits: 4.0 |
| Course Code | Course Name | Instructor(s) |
|---|---|---|
| CS2102 | Data Structures and Algorithms | Kripabandhu Ghosh |
| Syllabus |
|---|
| References |
|---|
| Text Book:
1. Artificial Intelligence A Modern Approach, by S. Russell. Norvig,PHI, Third Edition Reference Books: 1. A First Course in Artificial Intelligence by Deepak Khemani, McGraw Hill Education (India), 2013. 2. Artificial Intelligence by Kevin Knight, Elaine Rich, Third Edition 3. Artificial Intelligence: Foundations of Computational Agents by David L. Poole, Alan K. Mackworth 4. Machine Learning by Mitchell, Tom M., Indian Edition 5. Introduction to Machine Learning with Python: A Guide for Data Scientists by Andreas C. Mller, Sarah Guido |
Course Credit Options
| Sl. No. | Programme | Semester No | Course Choice |
|---|---|---|---|
| 1 | IP | 1 | Not Allowed |
| 2 | IP | 3 | Not Allowed |
| 3 | MP | 1 | Not Allowed |
| 4 | MP | 3 | Not Allowed |
| 5 | MR | 1 | Not Allowed |
| 6 | MR | 3 | Not Allowed |
| 7 | MS ( Computational and Data Sciences ) | 3 | Core |
| 8 | MS | 5 | Elective |
| 9 | MS | 7 | Elective |
| 10 | MS | 9 | Elective |
| 11 | RS | 1 | Not Allowed |
| 12 | RS | 2 | Not Allowed |