The Master of Science in Artificial Intelligence (MSAI) is an advanced, interdisciplinary graduate program designed to provide students with a deep theoretical understanding and practical expertise in the core principles and cutting-edge applications of AI. The curriculum typically covers machine learning, deep learning, natural language processing, computer vision, robotics, and the ethical implications of AI technology.
The MSAI program provides students with advanced knowledge in machine learning, deep learning, natural language processing, computer vision, and AI ethics. It prepares graduates to design, implement, and evaluate AI-driven systems for diverse domains such as healthcare, finance, robotics, and cybersecurity.
Covers ML, deep learning, NLP, computer vision, and reinforcement learning
Robotics, Business AI, or Healthcare AI tracks available
Students solve real-world AI problems in partnership with industry or labs
Our comprehensive curriculum is structured into different blocks. Each block combines theoretical foundations and practical applications:
| Code | Course title | Credits | Type |
|---|---|---|---|
| AI 501 | Foundations of Artificial Intelligence | 3 | Core |
| AI 502 | Machine Learning algorithms | 3 | Core |
| AI 503 | Deep Learning & Neural Networks | 3 | Core |
| AI 504 | Natural Language Processing | 3 | Core |
| AI 505 | AI Ethics, Policy & Society | 3 | Core |
| Credits required: 15 | |||
| Code | Course title | Credits | Type |
|---|---|---|---|
| AI 511 | Computer Vision & Image Processing | 3 | Core |
| AI 512 | Reinforcement Learning | 3 | Core |
| AI 513 | AI Research Methods & Capstone Project | 3 | Core |
| Credits required: 9 | |||
Choose one: 12 credits
| Code | Course title | Credits | Type |
|---|---|---|---|
| AI 620 | Robotics & Path Planning | 3 | Elective |
| AI 621 | Human-Robot Interaction | 3 | Elective |
| AI 622 | Multi-Agent Systems | 3 | Elective |
| AI 623 | Intelligent Control Systems | 3 | Elective |
| AI 630 | AI in Business Intelligence | 3 | Elective |
| AI 631 | Predictive & Prescriptive Analytics | 3 | Elective |
| AI 632 | AI for Financial Modeling | 3 | Elective |
| AI 632 | AI for Financial Modeling | 3 | Elective |
| AI 633 | AI for Supply Chain & Operations | 3 | Elective |
| AI 640 | AI in Healthcare Systems | 3 | Elective |
| AI 641 | Biomedical Signal Processing | 3 | Elective |
| AI 643 | Clinical Decision Support Systems | 3 | Elective |
| Credits required: 12 | |||
| Component | Credits |
|---|---|
| Core courses | 15 |
| Advanced AI core | 9 |
| Concentration Tracks | 12 |
| Total credits: 36 | |
Graduates of this program have pursued various rewarding career paths:
Design and build ML models, implement algorithms, and deploy them into production
Conduct original research to advance the field of AI, often within tech R&D labs or academia
To be considered for admission, applicants must meet the following requirements: