Master of Science in Artificial Intelligence - Computer Engineering Track
Program Overview
The Master of Science (MS) in Artificial Intelligence – Computer Engineering Track
prepares students to integrate and advance AI
methodologies within the domain of computer engineering. The curriculum emphasizes the design and implementation of intelligent systems,
smart technologies, and autonomous decision-making processes through machine learning, robotics, computer vision, and deep neural
networks. This 33-credit-hour program equips graduates with the analytical and computational expertise required for emerging careers in AI driven system design, advanced algorithm development, and intelligent automation across industries such as energy, defense, manufacturing,
and healthcare.
methodologies within the domain of computer engineering. The curriculum emphasizes the design and implementation of intelligent systems,
smart technologies, and autonomous decision-making processes through machine learning, robotics, computer vision, and deep neural
networks. This 33-credit-hour program equips graduates with the analytical and computational expertise required for emerging careers in AI driven system design, advanced algorithm development, and intelligent automation across industries such as energy, defense, manufacturing,
and healthcare.
Program Duration
The Joint MS in Artificial Intelligence (Computer Engineering Track) offers a flexible
pathway tailored to your pace and goals. The program requires completion of 11 courses
(33 credit hours, CH) and can be pursued full-time or part-time, with guidance from
the Graduate Coordinator to help you plan your degree. Current OSU ECE undergraduates
can accelerate their studies through the 4+1 pathway, applying up to 9 credit hours
toward both BS and MS degrees. Depending on your course load, you can earn your MS
in AI (CpE Track) in as little as one year or up to four years while balancing professional
and academic commitments.
- Why OSU ECE?
- Strong interdisciplinary collaboration between the School of Electrical and Computer Engineering and the School of Computer Science
- Jointly supported by a dynamic team of research-active and teaching-focused faculty dedicated to academic excellence and student success
- Access to state-of-the-art computing resources and modern laboratory facilities
- Flexible learning options with both in-person and online delivery formats
- Opportunities to engage in faculty-led research in Artificial Intelligence, Energy Systems, and Robotics
- Extensive industry partnerships providing pathways for internships, mentorship, and professional growth
- Career Pathways
Graduates are prepared for careers such as:
• AI & Machine Learning Engineer
• Data Scientist / Computer Vision Engineer
• Robotics & Intelligent Systems Engineer
• R&D Engineer in Smart Energy, Smart Manufacturing, Intelligent
Automation, and Semiconductor Design - Program Curriculum
Curriculum designed for individualized and self-paced learning.
CORE COURSES
9 Hours- CS 5723 Artificial Intelligence I
- CS 5783 Machine Learning
- ECEN 5733 Neural Networks
- ECEN 5773 Intelligent Systems
TRACK REQUIRED COURSES
6 Hours- ECEN 5513 Stochastic Systems
- ECEN 5743 Deep Learning
ELECTIVE COURSES*
18 Hours- CS 5793 Artificial Intelligence II
- CS 5683 Big Data Analytics
- ECEN 5283 Computer Vision
- ECEN 5243 Advanced Mobile Robotics
- ECEN 5453 Applied AI in Electrical and Computer Engineering
- ECEN 5793 Digital Image Processing
- Any core course not selected
ECEN 5080 Special Topics (up to 6 hrs)
Mobile Robotics, AI in Engineering
Applied Numerical Method with Python
for Engineers
*At least 12 hours of elective courses must be from Computer Engineering (ECEN)
TOTAL HOURS: 33