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AI-CPE

Why study a Master of Science in Artificial Intelligence with a Computer Engineering track online at OSU?

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.
Apply Request more information

Format

Online learning through the College of Engineering, Architecture and Technology (CEAT) provides a flexible alternative to traditional on-campus courses as a convenient way to earn your degree whenever your career or other life commitments prevent you from taking classes on campus in a traditional setting.

Online students utilize Canvas, OSU's online learning portal to watch lectures, turn in assignments and communicate with classmates and professors.

Courses taught online are of identical quality and instruction as those taught in traditional classrooms. CEAT Online Learning and the ECE faculty are here to help our students succeed!

Canvas Tutorial

Curriculum

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) and can be pursued full-time or part-time, with guidance from the Graduate Coordinator to help you plan your degree.


Program Requirements (33 credit hours)

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 total)

  • CS 5683 - Big Data Analytics

  • CS 5793 - Artificial Intelligence II

  • ECEN 5283 - Computer Vision

  • ECEN 5243 - Advanced Mobile Robotics

  • ECEN 5793 - Digital Image Processing

  • ECEN 5453 - Engineering Applications of Artificial Intelligence

Any core course not selected
ECEN 5080 - Special Topics (up to 6 hrs)
Mobile Robotics, AI in Engineering Applied Method with Python for Engineers
*At least 12 hours of elective courses must be from Computer Engineering (ECEN).

Admissions

Applications are accepted on a rolling basis. Applicants are strongly encouraged to submit application materials at least six months prior to the start of the semester.

Cost

Cost