Engineering Artificial Intelligence, Master of Engineering (M.Eng.)
Non-thesis only: 30 credits required
All Professional Master of Engineering Programs consist of 10 courses/30 credits. All students are expected to complete a preliminary course plan for their intended degree program. Degree planning worksheets can be found here: https://mage.umd.edu/degree-planning-sheets
| Course | Title | Credits |
|---|---|---|
| Engineering AI Required Core (take 4) | 12 | |
| Probability and Statistics for Engineering AI (Probability and Statistics for Engineering AI) | ||
| Numerical Methods for Engineering AI (Numerical Methods for Engineering AI) | ||
ENAI602 | (Foundations of Machine Learning for Engineering AI) | |
| Foundations of Data Science for Engineering AI (Foundations of Data Science for Engineering AI) | ||
| Engineering AI Core (choose 2) | 6 | |
ENAI604 | (Fair, Ethical and Sustainable Engineering AI) | |
| Generative Engineering AI (Generative Engineering AI) | ||
ENAI606 | (Large Language Models in Engineering AI) | |
| Python Applications for Engineering AI (Python Applications for Engineering AI and Cloud Engineering) | ||
| Fundamentals of AI and Deep Learning | ||
| Pre-Approved Technical Electives (choose 4) | 12 | |
| See Degree Planning Sheet for detailed course options. | ||
| Total Credits | 30 | |