Computer vision is a machine learning and artificial intelligence field focused on extracting useful information from images, video, and other visual data. Graduate study can cover image recognition, object detection, segmentation, neural networks, deep learning, and visual perception systems.
Our current inventory includes 8 master’s programs classified under computer-vision. We include programs only when computer vision has meaningful curriculum support rather than appearing as a single incidental elective.
Computer Vision Master’s Programs
| School | Location | Degree | Format | Tuition | Length |
|---|---|---|---|---|---|
| Avila University | Goodyear, AZ | MS in Technology Management: Artificial Intelligence | campus | $27,000 | Up to 24 months |
| Boston University MS in Artificial Intelligence | Boston, MA | MS in Artificial Intelligence | Campus | Est. $73,024 | 2–3 semesters |
| Colorado State University | Denver, CO | MS in AI and Machine Learning | online | $20,250 | 18 Months |
| East Texas A&M University | Commerce, TX | MS in Artificial Intelligence | Online or Campus | Est. $16,250 | 1.5–2 years |
| Mercer University MS in Data Science | Atlanta, GA | MS in Data Science | Online | Est. $26,316 | 18–24 months |
| Mercy University MS in Computer Science – Artificial Intelligence and Machine Learning | Dobbs Ferry, NY | MS in Computer Science – Artificial Intelligence and Machine Learning | Online, Hybrid, or Campus | Est. $41,292 | |
| University of Illinois Chicago Master of Engineering in AI and Machine Learning | Chicago, IL | Master of Engineering – AI and Machine Learning | Online | Est. $32,256 | 12 months |
| University of South Florida | Tampa, FL | Master of Science in Artificial Intelligence | Online or Campus | Approx $13.3K resident / $30.8K nonresident | 2 years |
What You Study in Computer Vision
Computer vision coursework often builds on machine learning, linear algebra, probability, optimization, and neural networks. Advanced study may cover convolutional neural networks, image classification, object detection, image segmentation, video analysis, feature extraction, and modern vision architectures.
The strongest programs connect these methods to practical projects or research. Applications can include robotics, autonomous systems, medical imaging, manufacturing, remote sensing, security, and visual search.
Computer Vision and Deep Learning
Modern computer vision relies heavily on deep learning. Neural networks can learn visual features directly from large image datasets and support tasks that once required extensive manual feature engineering. Students interested in computer vision should therefore check the depth of a program’s machine learning and deep learning curriculum.
How to Compare Computer Vision Programs
Check the curriculum depth. Look for multiple courses or a formal academic emphasis in computer vision, image processing, deep learning, or closely related visual computing topics.
Review prerequisites. Computer vision commonly requires strong programming, linear algebra, probability, and machine learning foundations.
Look at research and projects. Labs, faculty research, capstones, and applied projects can provide valuable experience with real visual datasets and modern models.
Compare cost and format. Use the program profiles above to review tuition, delivery format, degree length, admissions requirements, and the broader AI or machine learning curriculum.
Who Is Computer Vision Best For?
Computer vision can fit students who want to work with image and video data or build AI systems that interpret visual information. It is especially relevant to careers and research in robotics, autonomous technology, medical imaging, industrial inspection, geospatial analysis, and applied AI.