Master of Science (MS) in Artificial Intelligence – Computer Engineering Track

2 Years On Campus Masters Program

Oklahoma State University

Program Overview

The Master of Science in Artificial Intelligence – Computer Engineering Track at Oklahoma State University combines artificial intelligence, computer engineering, and advanced computing technologies to develop intelligent systems. Students gain practical expertise in machine learning, robotics, computer vision, neural networks, and deep learning, preparing for emerging careers in AI-driven engineering and automation.

Curriculum Structure

Year 1: Students establish core AI knowledge through courses such as Artificial Intelligence I (CS 5723), Machine Learning (CS 5783), Neural Networks (ECEN 5733), and Intelligent Systems (ECEN 5773). They also study Stochastic Systems (ECEN 5513) to develop mathematical and computational foundations.

Year 2: Students advance their specialization through Deep Learning (ECEN 5743), Computer Vision (ECEN 5283), Advanced Mobile Robotics (ECEN 5243), and Digital Image Processing (ECEN 5793). They can also explore Big Data Analytics and Applied AI in Electrical and Computer Engineering through electives.

Note: The program requires 33 credit hours, including 9 core credits, 6 track-required credits, and 18 elective credits. Completion may take one to four years depending on study pace.

Focus Areas

Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Computer Vision, Intelligent Systems, Robotics, Big Data Analytics, Digital Image Processing, Applied AI.

Learning Outcomes

AI system development, machine learning implementation, neural network design, deep learning applications, computer vision, intelligent automation, robotics applications, computational problem-solving, advanced data analysis.

Professional Alignment (Accreditation)

The program is jointly supported by the School of Electrical and Computer Engineering and the School of Computer Science. Specific professional accreditation for this master's degree is not stated on the official program page.

Reputation (Employability)

Industry and research opportunities: Students benefit from interdisciplinary faculty collaboration, modern computing facilities, research opportunities in AI and robotics, and industry partnerships offering internship and mentorship opportunities.

Experiential Learning (Research, Projects, Internships etc.)

Oklahoma State University's MSAI–Computer Engineering programme combines advanced technical coursework with research opportunities and access to modern computing resources. Students explore practical applications of artificial intelligence through machine learning, robotics, computer vision and intelligent automation. The programme's collaboration between Electrical and Computer Engineering and Computer Science also provides an interdisciplinary environment for developing AI solutions to engineering problems.

Practical Learning and Research Opportunities:

Faculty-Led AI Research: Students can engage in research activities with faculty working in Artificial Intelligence, Energy Systems and Robotics, gaining exposure to current engineering challenges and emerging technologies.
Machine Learning Applications: Through Machine Learning (CS 5783), students develop knowledge of algorithms and computational approaches used to identify patterns, analyse data and build predictive systems.
Neural Networks and Deep Learning: Courses such as Neural Networks (ECEN 5733) and Deep Learning (ECEN 5743) introduce techniques used in intelligent computing, image recognition and advanced AI applications.
Computer Vision: Computer Vision (ECEN 5283) and Digital Image Processing (ECEN 5793) provide opportunities to explore image analysis, visual recognition and automated interpretation of digital images.
Robotics and Autonomous Systems: Advanced Mobile Robotics (ECEN 5243) develops knowledge relevant to intelligent robotic platforms, navigation and autonomous decision-making.
Intelligent Systems Development: Through Intelligent Systems (ECEN 5773), students explore approaches for designing systems capable of processing information and supporting intelligent decisions.
Applied AI in Engineering: Applied AI in Electrical and Computer Engineering (ECEN 5453) connects AI methods with practical applications in electrical and computer engineering.
Computing and Laboratory Facilities: Students have access to modern laboratory facilities and computing resources that support advanced technical learning and research activities.

Progression & Future Opportunities

The M.S. in Artificial Intelligence – Computer Engineering Track prepares graduates for careers at the intersection of artificial intelligence, computing and engineering. Students develop advanced analytical and computational capabilities to build intelligent technologies, automate complex processes and develop AI-driven engineering solutions. The programme is relevant to industries increasingly adopting machine learning, robotics, computer vision and autonomous systems.

Career Opportunities:

AI Engineer: Design and implement artificial intelligence systems for automation, prediction, intelligent decision-making and engineering applications.
Machine Learning Engineer: Develop, train and optimise machine-learning models for analysing data and solving computational problems.
Data Scientist: Analyse complex datasets, develop predictive models and generate insights to support business and technical decisions.

Industry Sectors: Graduates can pursue opportunities in artificial intelligence and software development, semiconductor and electronics manufacturing, robotics, smart energy, defence technology, healthcare technology, intelligent manufacturing, automation, research and advanced computing.

Industry and Research Exposure: Oklahoma State highlights extensive industry partnerships that can support internship opportunities, mentorship and professional development. Faculty-led research in Artificial Intelligence, Energy Systems and Robotics also provides exposure to emerging technologies and engineering applications. These opportunities can help students connect advanced academic knowledge with industry requirements.

Professional Development: The programme's interdisciplinary structure encourages students to develop both computer science and computer engineering expertise. Access to modern computing facilities, research-active faculty and industry collaboration can help graduates strengthen their technical portfolios and prepare for specialist roles in AI development and intelligent engineering systems.

Flexible Study and Accelerated Pathway: Students can complete the programme full-time or part-time, with the university indicating a completion period ranging from one to four years depending on course load. Current Oklahoma State ECE undergraduate students may also use the 4+1 pathway, applying up to nine credits toward both bachelor's and master's degrees.

Further Academic Progression: Graduates interested in advanced research may pursue a Ph.D. in Electrical Engineering, Computer Engineering, Computer Science or a related discipline, depending on their research interests and admission requirements. The thesis option of the MSAI–CpE programme is particularly relevant for students planning doctoral study because it includes independent research in AI-related areas. Potential research directions include machine learning, neural networks, computer vision, robotics, intelligent systems and AI applications in energy and engineering.