Objective
Participants learn the fundamentals of artificial intelligence, machine learning, computer vision, and neural networks with emphasis using hands-on instruction resulting in a final capstone project.
Specialty areas of study in Electrical and Computer Engineering – AI Concentration include:
- Knowledge representation and reasoning
- Neural Networks
- Machine learning
- Data mining
- Computer vision
Industry Advisory Board
The MS program is informed by an industry advisory board with significant experience in electrical and computer engineering and AI.
Curriculum
Students enrolled in the MS in Electrical and Computer Engineering – Concentration in Artificial Intelligence must successfully complete 27 credits and a three-credit research project.
Required Courses
| Course # |
Title |
Credits |
| ECE 637 |
Principles of Artificial Intelligence |
3 |
| ECE 648 |
Machine Learning |
3 |
| ECE 653 |
Neural Networks |
3 |
| ECE 7xx |
Advanced Problems in AI (Capstone Course, topics vary) |
3 |
Electives – 18 credits
| Course # |
Title |
Credits |
| ECE 640 |
Digital Speech and Audio Processing |
3 |
| ECE 677 |
Data Mining |
3 |
| ECE 730 |
Statistical Learning |
3 |
| ECE 735 |
Fundamentals of Network Science |
3 |
| ECE 738 |
Computer Vision |
3 |
| ECE 753 |
Pattern Recognition and Neural Networks |
3 |
| CSC 650 |
Computational Neuroscience |
3 |
| CSC 749 |
Automated Reasoning |
3 |
| CSC 752 |
Autonomous Robotic Systems |
3 |
Students may select up to two elective courses other than the ones listed above in consultation with the academic advisor.
Admissions Information
