Artificial Intelligence, MAI
Program Description
The Master in Artificial Intelligence (MAI) at Utah Tech University is a professionally oriented graduate program designed to prepare students to address complex, real-world problems through the application of artificial intelligence (AI) and machine learning (ML) methodologies. The program emphasizes rigorous, project-based learning in high-demand domains such as computer vision, natural language processing, intelligent agents, and generative AI. Through applied coursework and faculty-mentored projects, students will develop advanced competencies in designing, implementing, and deploying end-to-end machine learning pipelines for industry-driven challenges. The program is designed for industry professionals seeking to design, implement, and deploy AI tools in practice, rather than preparing students for a PhD program.
The MAI builds directly on the Post-Baccalaureate Certificate in Applied Artificial Intelligence and Machine Learning, which comprises the first 15 credits of the program and serves as a stackable credential within the degree. Five foundational courses (three lecture-based and two project-based courses) are included in the certificate, which are listed in the table of program-required courses. Five additional advanced courses will be introduced in the second year, which extend the applied emphasis of the certificate by guiding students toward domain-specific implementations such as Natural Language Processing and Computer Vision. Advanced Deep Learning will cover state-of-the-art architectures and optimization strategies in other domains. Students will integrate and apply AI techniques to real-world problems in two consecutive project courses. This structure provides students with an interim, workforce-relevant credential while maintaining a clear pathway toward the completion of the full master’s degree. Compared with Utah Valley University’s M.S. in Applied AI program, which targets business and management professionals with no technical background, the MAI program focuses on students with computing skills and emphasizes hands-on, technical AI tool development (refer to the similar program table for details).
Admissions Requirements
Applicants must meet the following minimum requirements:
- Complete the online application.
- A bachelor’s degree from a regionally accredited institution in Computer Science, Engineering, Mathematics, or a related technical field. Or a bachelor's degree with a minimum of two years of Professional Software Development experience.
- English proficiency is required for applicants whose native language is not English, per Utah Tech graduate policy.
Students currently enrolled in the Post-Baccalaureate Certificate in Applied Artificial Intelligence and Machine Learning can progress into the MAI by submitting an internal form for program approval rather than a new application. The program will coordinate with Graduate Admissions and Operations to seamlessly enroll qualified certificate students in the master’s program. The program will admit students as cohorts each fall to promote collaboration and continuity through shared projects.
Program Curriculum
30 Credits
Required Courses
| Code | Title | Hours |
|---|---|---|
| CS 6300 | Principles of Artificial Intelligence | 3 |
| CS 6310 | Foundations of Machine Learning | 3 |
| CS 6320 | Foundations of Deep Learning | 3 |
| CS 6350 | Artificial Intelligence and Machine Learning Project 1 | 1-3 |
| CS 6351 | Artificial Intelligence and Machine Learning Project 2 | 1-3 |
| CS 6321 | Natural Language Processing | 3 |
| CS 6322 | Computer Vision | 3 |
| CS 6323 | Advanced Deep Learning | 3 |
| CS 6352 | Artificial Intelligence and Machine Learning Project 3 | 1-3 |
| CS 6353 | Artificial Intelligence and Machine Learning Project 4 (Capstone) | 1-3 |
Elective Course
| Code | Title | Hours |
|---|---|---|
| CS 6359R | Artificial Intelligence and Machine Learning Independent Project | 1-3 |
Graduation Requirements
- The Master of Artificial Intelligence (MAI) will require completion of 30 graduate credit hours. The program is designed to be completed in six semesters (two calendar years) under a cohort model.
- Maintain a 3.0 cumulative GPA in all graduate coursework.
- Complete all coursework with a B- or higher.
- At least 20 credits at Utah Tech University for residency.
NB: Up to 10 credits earned at an accredited institution may be transferred toward the degree upon program approval. Allowing limited transfer credit supports students transitioning from related graduate study while preserving Utah Tech’s academic standards. The 30-credit total includes six lecture-based courses (18 credits) and four project-based courses (12 credits). The capstone will be the last project course (AI/ML project 4), with increased rigor that is cumulative across the series of project-based courses, without a separate standalone requirement. The delivery modality will be HyFlex.