MEng in AI Curriculum
Curriculum Overview
MEng Program
The MEng program requires 12 course credits in AI/ML foundations, 12 credits in domain intersection in biomedicine (typically courses in BME), and 6 credits for Knowledge Extensions. Students are required to take at least two BME courses.
Foundational courses list (12 credits required):
- EECS 545: Machine Learning
- CSE 592: Foundations of Artificial Intelligence
- EECS 551: Matrix methods in SIPML
- EECS 505: Computational Data Science & ML
- ECE 553: Machine Learning
- EECS 453: Principles of Machine Learning
- ECE 559: Optimization methods in SP and ML
- ECE 567: Reinforcement Learning
- BIOMEDE 487: Artificial Intelligence in Biomedical Engineering
Domain Intersection courses list (12 credits required):
- BIOMEDE 487: Artificial Intelligence in Biomedical Engineering
- BIOMEDE 503: Statistical Methods for Biomedical Engineering
- BIOMEDE 517: Sensing and Machine Learning for Neural Interfaces
- BIOMEDE 599: Deep Learning for Signal and Image Processing
- BIOMEDE 599.017: AI for Experiment Design (residential format only)
- EECS 598: Artificial Intelligence in Biomedicine
Knowledge Extensions (6 credits). Any BIOMEDE or College of Engineering course
MENg in AI Sample Plan of Study
AI/ML Fundamentals (12 credits)
EECS 551: Matrix Methods for Signal, Image Processing
EECS 553: Machine Learning
EECS 559. Optimization Methods in Signal Processing and Machine Learning
ECE 567: Reinforcement Learning
Domain Intersections (12 credits)
BIOMEDE 487: Artificial Intelligence in Biomedical Engineering
BIOMEDE 503: Statistical Methods for Biomedical Engineering
BIOMEDE 517: Sensing and Machine Learning for Neural Interfaces
BIOMEDE 599: Deep Learning for Signal and Image Processing
Knowledge Extensions (6 credits)
BIOMEDE 599: AI for Experiment Design
EECS 598: Artificial Intelligence in Biomedicine
Graduate Certificate Program in AI
The Graduate Certificate Program requires 6 credits in AI/ML Fundamentals Core Courses and 6 credit hours of Domain Intersection Courses from the list above (at least two BIOMEDE courses).
Sample Plan of Study
AI/ML Fundamentals (6 credits)
BIOMEDE 487: Artificial Intelligence in Biomedical Engineering
EECS 553: Machine Learning
Domain Intersections (6 credits)
BIOMEDE 517: Sensing and Machine Learning for Neural Interfaces
BIOMEDE 599: Deep Learning for Signal and Image Processing
Notes:
1. All the courses listed above, except BIOMEDE 599.017 (AI for Experiment Design), are available in both residential and online formats.
2. Individualized plans of study will be developed by students in consultation with an advisor.
3. Refer to the Engineering Course Guide and Bulletin for course descriptions.
4. Students in the BME concentration for both the certificate and MEng programs are required to take at least two BME courses
5. BIOMEDE 487 can count towards either AI fundamentals or Domain Intersection but not both.