Curriculum
The MSAI program consists of 30 credit hours. The seven courses (21 credits) consist of six lecture courses and one graduate project. The lecture courses provide the students with AI knowledge, and the graduate project will be managed as a directed study course, that can be composed of student teams of two or three members guided by the faculty. Students may enroll in the graduate project after the completion of the six (6) core courses and concurrently with the specialization courses.
The students will select three courses (nine credits) from a specialization. The program will start with specializations in “Connected Vehicles” from the ECE Department and “Data Science” from the MCS Department. Future planned specializations are included in the list below to communicate the long-term goals of the program.
- Connected Vehicles consisting of Connected Vehicle Technologies, Computer Vision, and Advanced Deep Learning
- Data Science consisting of Machine Learning and Neural Networks, Social Network Mining, Text Mining and Analytics, and Applied Machine Learning
- Robotics and Sensors consisting of Bioinspired Robotics, Interface and Control of Robotics, Application of Artificial Intelligence, Intelligent Robotics with ROS
- Cybersecurity consisting of Computer Network Cyber Security, Embedded Networking, Computer Networking, Cybersecurity, Management Information Systems.
The graduate project will serve as a practicum and a practical excursion building AI application or a graduate project in AI.
Complete six (6) lecture courses and one (1) graduate project:
| Course Name | Course # | Credits |
|---|---|---|
| Software Development for AI | EEE 5513 | 3 |
| Machine Learning and Pattern Recognition | MCS 5623 | 3 |
| Digital Signal Processing | EEE 5653 | 3 |
| Theory of Computation | MCS 5243 | 3 |
| Artificial Intelligence | MCS 5323 | 3 |
| Deep Learning for Engineers | EEE 5523 | 3 |
| Algorithm Design and Analysis | MCS 5803 | 3 |
| Graduate Project | MCS/EEE/MRE/EME 6xx3 | 3 |
Specialization I. Choose three (3) of the following Robotics and Sensors courses:
| Course Name | Course # | Credits |
|---|---|---|
| Bioinspired Robotics | EME 5983 | 3 |
| Interface and Control of Robotics | EEE 5563 | 3 |
| Application of Artificial Intelligence | EEE 5553 | 3 |
| Intelligent Robotics with ROS | MCS 5403 | 3 |
| Mechatronics Systems I | MRE 5183 | 3 |
| Modern Controls Systems | MRE 5323 | 3 |
Specialization II. Take the three (3) following Connected Vehicles courses:
| Course Name | Course # | Credits |
|---|---|---|
| Connected Vehicle Technologies | EEE 5533 | 3 |
| Computer Vision | EEE 5353 | 3 |
| Adv. Deep Learning for Engineers | EEE 6523 | 3 |
Specialization III. Choose three (3) of the following Data Science courses:
| Course Name | Course # | Credits |
|---|---|---|
| Deep Learning and Neural Networks | MCS 5713 | 3 |
| Social Network Mining | MCS 5723 | 3 |
| Text Mining and Analytics | MCS 5993 | 3 |
| Applied Machine Learning | MRE 5xx3 | 3 |
Specialization IV. Take the three (3) following Cybersecurity courses:
| Course Name | Course # | Credits |
|---|---|---|
| Computer Network Cyber Security | EEE 5443 | 3 |
| Embedded Networking | EEE 5453 | 3 |
| Computer Networking | EEE 5463 | 3 |
| Mgt. Info. Systems | INT 6043 | 3 |
| Cybersecurity | INT 7223 | 3 |
Supporting files for download
M.S. AI Curriculum Flowchart
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