Degree Requirements
A minimum of 30 credit hours beyond a bachelor’s degree is required. These hours may include coursework completed as part of the MSADS master’s program at the University of Florida or, with approval, up to 9 credit hours from a master’s program at another accredited institution. Any course substitutions must be formally petitioned and are reviewed individually on a case-by-case basis.
Requirements include completion of the following:
- MSADS core courses: 21 credits
- MSADS elective courses: 6 credits
- MSADS capstone project: 3 credits
Curriculum
A standard 4-semester plan of study will look like the following:
- EGN 5447 Mathematical Foundations for Data Science for Engineers I (3 credits)
(Typically offered in Fall) - EGN 5442 Programming for Applied Data Science (3 credits)
(Typically offered in Fall) - EGS 6216 AI Ethics for Tech Leaders (3 credits)
(Typically offered in Fall and Spring)
- CAP 5771 Introduction to Data Science (3 credits)
(Typically offered in Spring) - EGN 6446 Mathematical Foundations for Data Science for Engineers II (3 credits)
(Typically offered in Spring) - EEE 5776 Applied Machine Learning (3 credits)
(Typically offered in Spring)
- EEE 6778 Applied Machine Learning II (3 credits)
(Typically offered in Fall)
Choose two (2) elective courses in one of the following specializations:
Agricultural and Biological Engineering
- ABE 5038 Fundamentals and Applications of Biosensors (3 credits)
(Typically offered in Spring) - ABE 5643C Biological Systems Modeling (3 credits)
(Typically offered in Fall) - ABE 6649C Advanced Biological Systems Modeling (3 credits)
(Typically offered in Spring)
Artificial Intelligence (AI)
- ESI 6617 High-Dimensional Data Analytics (3 credits)
(Typically offered every other Spring, next available Spring 2026) - EEE 6512 Image Processing and Computer Vision (3 credits)
(Typically offered in Spring)
Biomedical
- BME 6522 Biomedical Multivariate Signal Processing (3 credits)
(Typically offered in Spring) - BME 6938 Multimodal Data Mining (3 credits)
(Typically offered in Spring)
Chemical Engineering
- ECH 6845 Chemical Process Data Science (3 credits)
(Typically offered in Fall) - ECH 6937 Fundamentals of Artificial Neural Networks (3 credits)
(Typically offered in Fall)
Data Analytics in Industrial Systems Engineering (ISE)
- EIN 6905 Data Analytics for Systems Monitoring (3 credits)
(Currently not on the schedule) - ESI 6617 High-Dimensional Data Analytics (3 credits)
(Typically offered every other Spring, next available Spring 2026)
Engineering Education
- EGS 6020 Research Design in Engineering Education (3 credits)
(Typically offered in Fall) - EGS 6012 Research Methods in Engineering Education (3 credits)
(Typically offered in Spring)
Environmental
- OCP 6168 Data Analysis Techniques for Coastal Ocean (3 credits)
(Typically offered in Fall) - ABE 6035 Advanced Remote Sensing: Science and Sensors (3 credits)
(Typically offered in Fall) - EEE 6512 Image Processing and Computer Vision (3 credits)
(Typically offered in Spring)
Transportation
- EGN 5215 Machine Learning Applications in Civil Engineering (3 credits)
(Typically offered in Fall) - OCP 6168 Data Analysis Techniques for Coastal Ocean (3 credits)
(Typically offered in Fall)
Other pre-approved course electives:
Agricultural and Biological Engineering
- ABE 6933 Computer Vision& Deep Learning (3 credits)
(Typically offered in Fall) - ABE 6933 Systems Thinking in Food Systems (3 credits)
(Typically offered in Fall) - ABE 6933 Data Visualization & Dashboards in Agriculture (3 credits)
(Typically offered in Fall)
Biomedical
- CAP 5510 Bioinformatics (3 credits)
(Typically offered in Fall)
Data Analytics in Industrial Systems Engineering (ISE)
- ESI 6616 Data Analytics for System Monitoring (3 credits)
(Typically offered in Fall) - ESI 6325 Applied Probability Methods in Engineering (3 credits)
(Typically offered every other Fall, next offering Fall 2026)
Environmental
- ENV 6932 Artificial Intelligence and Machine Learning for Engineering Applications (3 credits)
(Typically offered in Fall) - ABE 6031 Instrumentation in Agricultural Engineering Research (3 credits)
(Typically offered in Fall)
All specializations
- EGN 6951 Integrated Product and Process Design G1 (3 credits)
(Typically offered in Fall) - EGN 6XXX Practical Work in Applied Data Science (3 credits)
(Available in Summer, Fall & Spring)
- EGN 6933 Project in Applied Data Science (Non-Thesis Project) (3 credits)
(Typically offered in Fall and Spring)
Syllabi
For the up-to-date syllabi for each course, please visit the respective course’s website:
| Course Code | Department | Website |
| ABE | Agricultural and Biological Engineering | https://abe.ufl.edu/graduate/courses/ |
| EIN, ESI | Industrial and Systems Engineering | https://www.ise.ufl.edu/academics/syllabi-upload/ |
| EEE, EEL | Electrical & Computer Engineering | https://www.ece.ufl.edu/academics/course-syllabi/ |
| BME | Biomedical Engineering | https://bme.ufl.edu/academics/bme-graduate-program/course-listing/ |
| CAP, CEN | Computer & Information Science & Engineering | https://www.cise.ufl.edu/academics/course-syllabi/ |
| ECH | Chemical Engineering | https://che.ufl.edu/academics/course-schedule-syllabi/ |
| EGS, EGN | Engineering Education | https://eed.eng.ufl.edu/course-syllabi/ |
| ENV, OCP | Engineering School of Sustainable Infrastructure & Environment | https://www.essie.ufl.edu/resources/essie-course-syllabi/ |
| EML | Mechanical Engineering | https://mae.ufl.edu/students/course-syllabi/ |