Degree Requirements
At least 30 credit hours beyond bachelor’s degree are required. These hours include MSAIS master’s degree work taken at the University of Florida or, if approved, up to 9 hours of master’s degree work earned at another approved university outside UF. Course substitutions must be petitioned and are considered on a case-by-case basis.
Requirements include completion of the following:
- MSAIS core courses: 18 credits
- MSAIS specialization courses: 9 credits
- MSAIS Capstone Project: 3 credits
Curriculum
A standard 4-semester curriculum will look like the following:
- Core 1: Machine Learning.
- EGN5216 Machine Learning for AI Systems (3 credits)
- Core 2: AI Systems.
- EGN 6216 Artificial Intelligent Systems (3 credits)
- Core 3: Sensing &Analysis (select 1 of these 3 options).
- EEE 6512 Image Processing and Computer Vision (3 credits)
- EEL 5406 Computational Photography (3 credits)
- CAP 5416 Computer Vision (3 credits)
- Core 4: Security (select 1 of these 3 options).
- CIS 6930 Trustworthy Machine Learning (3 credits)
- EEE 6561 Fundamentals of Biometric Identification (3 credits)
- EEL 5729 IoT Security and Privacy (3 credits)
- CORE 5: Deep Learning (select 1 of these 2 options)
- CAP 6615 Neural Networks for Computing (3 credits)
- EGN 6217 Applied Deep Learning (3 credits)
- CORE 6: Ethics (select 1 of these 2 options)
- EGN 6933 AI Ethics for Tech Leaders (3 credits)
- LAW 6930 Legal, Policy, and Ethical Dimensions (3 credits)
Choose three (3) elective courses, at least one (1) in AML-DDM and one (1) in AR-HCC:
Advanced Machine Learning and Data Driven Modeling (AML-DDM)
- BME 6928 Biomedical Data Science (3 credits)
- EEL 5840 Fundamentals of Machine Learning (3 credits) or STA 6703 Statistical Machine Learning (3 credits)
- CAP 6617 Advanced Machine Learning (3 credits)
- EEL 6814 Neural Networks and Deep Learning (3 credits)
- EEL 6825 Pattern Recognition and Intelligent Systems (3 credits)
- ESI 6492 Global Optimization (3 credits)
- EEE 6504 Machine Learning for Time Series (3 credits)
- ESI 6355 Decision Support Systems for ISE (3 credits)
Autonomy, Robotics, and Human-Centered Computing (AR-HCC)
- ABE 6005 Applied Control for Automation and Robotics (3 credits)
- CAP 5108 Research Methods for Human Centered Computing (3 credits)
- CEN 5726 Natural User Interaction (3 credits)
- EML 6351 Adaptive Control (3 credits)
Unrestricted Technical Electives (UT)
This group allows the students to take a technical elective course for greater curriculum flexibility. The technical elective courses in this group must be chosen in coordination with the graduate advisor to ensure prerequisite fulfillment and to optimize for achieving student career goals (e.g., courses related to entrepreneurship).