About
The AI Minor is designed to equip students with foundational knowledge in artificial intelligence and machine learning principles. The coursework is structured to provide students with the essential knowledge and core skills needed to apply AI and machine learning techniques to address a wide range of practical problems. Students completing the minor will gain a comprehensive understanding of AI and machine learning principles, methodologies, and algorithms, equipping them with the ability to create AI-driven solutions for real-world challenges. This minor is ideal for undergraduates with solid quantitative backgrounds eager to learn and apply AI and machine learning fundamentals.
The minor is intended for students in computing majors, specifically computer science, computer engineering, software engineering, and data science. The Undergraduate Minor consists of 9 credit hours of core AI courses and 6 credit hours of elective AI-related courses.
To take the courses in the minor, students would need Com S 3110 as a prerequisite, a course required by all computing majors.
Required Courses
| Course ID | Course Name |
|---|---|
| PHIL 3430 | Philosophy of Technology |
| COM S 4720 | Principles of Artificial Intelligence |
| COM S 4740 | Introduction to Machine Learning |
Electives
| Course ID | Course Name |
|---|---|
| CPR E 4190 | Software Tools for Large Scale Data Analysis |
| EE 4240 | Introduction to Digital Signal Processing |
| EE 4250 | Machine Learning: A Signal Processing Perspective |
| M E 4250 | Optimization Methods for Complex Designs |
| M E 4560 | Machine Vision |
| M E 4750 | Modeling and Simulation |
| COM S 4350 | Algorithms for Large Data Sets: Theory and Practice |
| COM S 4710 | Responsible AI |
| COM S 4760 | Motion Planning for Robotics and Autonomous Systems |
| COM S 4770 | Foundations of Robotics and Computer Vision |
| STAT 4740 | Intro to Bayesian Data Analysis |
Contact Us
For more information about the minor in Artificial Intelligence, please contact: