ADAN 7603 AI Algorithms II
This course aims to teach students advanced AI algorithms and covers neural networks, deep learning architectures, and reinforcement learning. The course provides a high-level theoretical overview of each section and discusses practical applications through hands-on projects. The course uses Python as the programming language. Prerequisites: Data analysis and feature engineering, traditional machine learning theory and practice, python programming (intermediate level e.g., familiarity with sci-kit learn, matplotlib, NumPy, pandas), linear algebra, and first-order derivatives.
Course overview
- Department
- Advancing Studies
- School
- ADV
- Credits
- 3
- Level
- Graduate
- Offered
- Periodically
Catalog details
Course evaluations
- Course rating
- 3.10 / 5 · Good
- Instructor rating
- 3.09 / 5 · Good
- Terms evaluated
- 8
| Term | Instructor | Course overall | Instructor overall | Well organized | Clear learning objectives | Intellectually challenging | Helpful assignments | Applicable beyond course | Attendance necessary | Weekly effort | Responses |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Spring 2026 | Kishore Mosaliganti | 3.8 | 3.9 | 4.0 | 4.1 | 4.3 | 4.3 | 4.0 | 3.7 | 7–9 hrs/week | 12 of 15 |
| Fall 2025 | Kishore Mosaliganti | 3.3 | 3.3 | 3.7 | 3.6 | 3.9 | 3.5 | 3.5 | 3.0 | 7–9 hrs/week | 12 of 17 |
| Summer 2025 | Kishore Mosaliganti | 3.3 | 3.3 | 4.3 | 4.3 | 4.5 | 4.2 | 4.2 | 4.0 | 10+ hrs/week | 6 of 7 |
| Spring 2025 | Kishore Mosaliganti | 2.7 | 2.8 | 3.4 | 4.0 | 4.1 | 3.5 | 4.1 | 2.9 | 10+ hrs/week | 14 of 19 |
| Fall 2024 | Kishore Mosaliganti | 2.9 | 2.7 | 3.6 | 4.1 | 4.0 | 4.0 | 4.2 | 3.4 | 7–9 hrs/week | 18 of 26 |
| Summer 2024 | Kishore Mosaliganti | 3.0 | 3.0 | 4.1 | 3.9 | 4.1 | 3.9 | 3.6 | 4.0 | 10+ hrs/week | 7 of 9 |
| Spring 2024 | Kishore Mosaliganti | 3.5 | 3.4 | 3.6 | 3.8 | 4.0 | 4.3 | 4.1 | 3.3 | 7–9 hrs/week | 8 of 14 |
| Fall 2023 | Kishore Mosaliganti | 2.5 | 2.7 | 3.4 | 3.7 | 4.3 | 3.9 | 3.8 | 4.0 | 10+ hrs/week | 12 of 12 |