Master of Engineering in Artificial Intelligence for Computer Vision and Control
AI has become a valuable and important catalyst for other technologies such as the Internet of Things and Cyber Physical Systems. AI is also considered as the engine that powers several truly ground-breaking Computer Vision, Control and Cybernetic applications such as autonomous cars, robotic personal assistants and automated manufacturing. The Master of Engineering in Artificial Intelligence, Computer Vision and Control degree is intended to provide interested students maximum exposure towards the very fast evolving AI technologies, machine learning, and methods while particularly targeting Electrical and Computer Engineering topics such as computer vision, medical image diagnosis, power system distribution, robotics and automation. Today, all major new technology products inherit a layer of artificial intelligence unit for self-learning and adaptability. Depending on the application or platform, this AI component can be used for speech recognition, face recognition or context-aware human-device interactions. The wide use of these AI technologies resulted in a major spike in the demand for engineers who are trained in this dynamic and fast-growing exciting field. Through the Master of Engineering in Artificial Intelligence, Computer Vision and Control students will be ready to overcome challenges in the field of core AI framework, signal & image processing and computer vision, control systems, embedded systems, integrated circuits and VLSI including neuromorphic computing, network, communication and information systems, power systems and robotics.
Minimum Credits Required | 30 |
Maximum 400-Level Credit | 12 |
Minimum 500-Level+ Credit | 18 |
Maximum 700-Level Credit | 4 |
Maximum Transfer Credit | 9 |
Code | Title | Credit Hours |
---|---|---|
Required Courses | (15-16) | |
Select minimum 5 courses from the following: | 15-16 | |
Digital Signal Processing I | 3 | |
or ECE 569 | Digital Signal Processing II | |
Control Systems | 3 | |
or ECE 533 | Robust Control | |
AI and Edge Computing | 3 | |
IoT and Cyber Physical Systems | 3 | |
AI in Smart Grid | 3 | |
Compt Vision Image Processing | 3 | |
Machine and Deep Learning | 3 | |
Object-Oriented Program & ML | 3 | |
Special Problems (Artificial Intelligence, Computer Vision and Control) | 1-3 | |
Signal and Image Processing Elective | (3) | |
Select a minimum 1 course from the following: | 3 | |
Digital Signal Processing I | 3 | |
Image Processing | 3 | |
Video Processing & Comm | 3 | |
Analysis Random Signals | 3 | |
AI in Smart Grid | 3 | |
Compt Vision Image Processing | 3 | |
Machine and Deep Learning | 3 | |
Statistical Signal Processing | 3 | |
Digital Speech Processing | 3 | |
Digital Signal Processing II | 3 | |
Computer Engineering Elective | (3) | |
Select a minimum 1 course from the following: | 3 | |
Intro to Computer Ntwks | 3 | |
Smart & Connected Embedded Sys | 4 | |
AI and Edge Computing | 3 | |
IoT and Cyber Physical Systems | 3 | |
Wireless Ntwrk Protocols/Stand | 3 | |
Computer Cyber Security | 3 | |
Info Theory and Applications | 3 | |
Application Software Design | 3 | |
Comm Netwrks Performance Analy | 3 | |
Computer Network Security | 3 | |
Modern Internet Tech | 3 | |
Computer Org and Design | 3 | |
Hardwr Security & Adv Comp Arc | 3 | |
Hardware Software Codesign | 3 | |
Object-Oriented Program & ML | 3 | |
Power and Control Engineering Elective | (3) | |
Select a minimum 1 course from the following: | 3 | |
Power Electronics | 4 | |
Control Systems | 3 | |
Applied Optimization Engrgs | 3 | |
Hybrid Electric Vehicle Drives | 3 | |
Robust Control | 3 | |
Next Generation Smart Grid | 3 | |
Motion Control Syst Dynamics | 3 | |
Power Elect Dynmcs Control | 3 | |
Advanced Power Electronics | 3 | |
Adjustable Speed Drives | 3 | |
Power Market Operations | 3 | |
Fault Tolerant Power Systems | 3 | |
Power System Reliability | 3 | |
Power Syst Dynamics Stability | 3 | |
Cntrl Oprtn Elect Power Systs | 3 | |
Oper/Plan/Dist Power Grid | 3 | |
Elements of Sustainable Energy | 3 | |
Elements of Smart Grid | 3 | |
Microgrid Design and Operation | 3 | |
Elective Courses | (5-6) | |
The remaining elective courses may be chosen from any of the listed core or elective options, provided that those courses were not already used to satisfy another degree requirement. | 5-6 |