Artificial Intelligence (MS)
Offered by the Department of Computer Science, in partnership with the Department of Mathematics and Statistics, College of Arts and Sciences.
Admission to Program
In addition to meeting the minimum university requirements for graduate study, applicants are expected to have proficiency in Python, familiarity with data structures, algorithms, and basic software development practices, and completion of Calculus I, Calculus II, Intermediate Statistics, Linear Algebra or course equivalents. Prerequisites may be waived for qualified persons with comparable experience.
Students who lack preparation in one or two areas will be required to complete pre-requisite courses to be ready for every course they take. Courses may be taken at the graduate level and counted towards the MS degree with approval of the program.
Degree Requirements
- 30 credit hours of approved graduate work
- Capstone Experience: Complete 3 credit hours of internship or directed research from one of the following:
Course Requirements
Core (12 credit hours)
- CSC-668 Artificial Intelligence (3)
- CSC-683 Cloud Computing and Machine Learning (3)
- DATA-645 Neural Networks and Deep Learning (3)
- ETHC-630 AI Ethics (3)
STAT-627/CSC-680 (3 credit hours)
Complete 3 credit hours from the following:
Note: With advisor approval, students demonstrating prior knowledge of supervised and unsupervised learning may substitute DATA-642 for CSC-680 or STAT-627.
Track (9 credit hours)
Complete 9 credit hours from one of the following tracks
Mathematical Foundations of AI
Complete 9 credit hours from the following, or other graduate courses approved by advisor:
- CSC-660 Tools of Scientific Computing (3)
- DATA-642 Advanced Machine Learning (3)
- MATH-631 Information Theory (3)
- MATH-665 Numerical Analysis: Basic Problems (3)
- STAT-630 Mathematical Statistics I (3)
- STAT-631 Mathematical Statistics II (3)
- STAT-684 Introduction to Stochastic Processes (3)
AI Methods and Advanced Applications
Complete 9 credit hours from the following, or other graduate courses approved by advisor:
Science and Technology (3 credit hours)
Complete 3 credit hours from the following, or other courses in physics, biology, chemistry, computational science, or other STEM areas approved by advisor:
- BEHS-710 Sustainable Systems of Drug Development: One Health Initiative (3)
- BIO-601 Mechanisms of Pathogenesis (3)
- ENSC-654 Geographic Information Systems (3)
- ENSC-655 Environmental Geographic Information Systems (3)
- HLTH-615 Science of Health Promotion and Disease Prevention (3)
- HLTH-683 Data Analysis in the Health Sciences (3)
- PHYS-660 Statistical Mechanics (3)
- PHYS-665 Computational Modeling for Science and Engineering (3)
- PHYS-675 Quantum Information and Computation (3)
Capstone (3 credit hours)
Complete 3 credit hours of internship or directed research from one of the following: