Artificial Intelligence Master's Program
Reputation
Study with leading experts working in AI today at one of the top-ranked computer science programs in the nation.
Lab-Based Learning
Industry-oriented, hands-on learning in state-of-the-art facilities.
Campus Community
Be part of a challenging but collaborative culture that empowers you to achieve your goals.
Location
Access the Denver-Boulder tech corridor, one of the nation most entrepreneurial ecosystems.
Faculty Reviews
In a world increasingly run by intelligent systems, expertise in AI will be the difference between keeping up and leading the way. A master in artificial intelligence will empower students to design ethical, responsible machine learning solutions that scale across platforms — from healthcare and finance to social media and robotics. It more than technical skill; it a commitment to shaping AI that amplifies human potential.
Kevin Gifford
Research Professor and MS-AI Faculty Director
Choose Your Pathway in Artificial Intelligence
We offer two exciting tracks to help you achieve your goals and advance your career.
Master's
On-campus
Semester-based
2 years
30 credits
Professional internships available
MS from Coursera
100% online
Self-paced, with 8-week courses
Varies, possible in 12 months
30 credits
No internships available
Not sure which path is right for you? Contact our graduate advisors for the or to discuss your career goals and determine the best fit.
What You'll Learn
Our professional master will ground you in the relevantmathematical and algorithmic foundations, ethics, applied AI and machine learning skills you’ll need to succeed as an AI engineer. Depending on your interests, you’ll take interdisciplinary courses in mathematics, philosophy, information science, business analytics and spatial analytics. You’ll also take electives in advanced robotics, data mining, natural language processing, neural networks and deep learning.
The online master from Coursera will help you develop expertise in scalable AI infrastructure, distributed training, model parallelism and deployment on specialized hardware. You’ll explore the ethical implications of AI, immerse yourself in machine learning best practices, and learn how to optimize AI models for performance. You can combine your core curriculum courses with other ϾƷ degrees, such as electrical engineering, engineering management and data science.
Faculty Spotlights
Costs & Financial Information
A master's degree from the College of Engineering and Applied Science represents a valuable investment in your career potential. While costs vary by program, residency status and enrollment type, we're committed to transparency in helping you plan for this important step.
- Tuition structure: Engineering master's programs have different rate structures based on program type, delivery method and course load
- ROI consideration: Most graduates recoup their educational investment within 2.5 years of completing their degree
- Flexible options: Many programs offer part-time enrollment, allowing you to distribute costs while maintaining employment
- Scholarships and fellowships: Program-specific opportunities are rare, and funding for master students is not guaranteed; master students should plan on providing their own resources to finance their education
- Assistantships: Professional master students are not eligible for teaching or research assistantships, but are eligible for on-campus hourly positions that do not include tuition remission
- Employer benefits: Many companies provide tuition assistance for job-relevant graduate education
- Military benefits: Veterans and active-duty military personnel can utilize GI Bill benefits for qualified programs
For detailed, current information about costs specific to your program of interest and payment options, we recommend visiting the ϾƷ Bursar's Office.
Admissions Requirements & Application Information
The following apply to the on-campus professional MS in AI:
- Bachelor's degree from an accredited institution with a minimum 3.0 GPA.
- Your prior studies must include at least three, one-semester courses in computer science. Courses should cover programming requirements, software requirements (computer systems or software tools and methods or principles of programming languages), and theory (data structures and algorithms).
- Your prior studies must include at least three, one-semester courses in mathematics. This can include calculus, differential equations, linear algebra, probability, statistics and abstract algebra, that indicate your mathematical maturity.
- Statement of purpose outlining your goals and interests.
- Three letters of recommendation.
- Official transcripts.
- Resume/CV highlighting relevant experience.
Visit the computer science admissions page to learn more about prerequisites for computer science and non-computer science majors.
- Fall admission: Dec. 15
- We do not offer spring admissions.
- Whether you’re a US citizen or international applicant, the computer science admissions page contains all the relevant information and links you’ll need to submit your application electronically.
- All applications are evaluated by faculty in the spring and admissions decisions are announced by the end of March.
- Note: This program is not currently open to international applicants.
Explore Related Programs
If you’re not sure this is the program for you, we offer several related degrees for you to consider:
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