Artificial Intelligence - Master of Science

Artificial Intelligence (AI) technologies are rapidly evolving and being more integrated into various aspects of society and industry, leading to a growing demand for Artificial Intelligence professionals. The Master of Science in Artificial Intelligence will combine technical courses in the fundamentals of AI and courses that address the interaction between AI and humans and society. During their coursework, students will build solid foundations in mathematics, statistics and computing and also obtain a broader view of human-centered AI and its societal implications. Students will gain expertise in machine learning, deep learning, and AI-driven decision-making while exploring areas such as AI ethics, human-computer interaction, explainable AI, and policy considerations. The program prepares graduates to develop AI solutions that enhance human well-being, promote fairness, and integrate seamlessly into social and professional contexts. The program is offered through the Science Academy, in conjunction with the Artificial Intelligence Interdisciplinary Institute at Maryland, in the College of Computer, Mathematical, and Natural Sciences.

The MS in AI consists of 30 credits of coursework, is a non-thesis program, and can be completed in less than 2 years. The program emphasizes practical knowledge and applied learning and does not offer research opportunities. Students will be prepared for careers across disciplines and they will develop skills to be collaborative, adaptable problem solvers in a rapidly changing field. The program features instructional delivery through face-to-face instruction at the UMD College Park campus, mostly in the evenings to accommodate working professionals. 

Application Deadlines

Fall 2025
Domestic: August 15, 2025

Fall 2026
International and domestic applications will be available in August 2025.

Application Coming Soon!

Any student applying for admission to a graduate program at the University of Maryland must meet the following minimum admission criteria as established by the Graduate School.

  • Applicants must have earned a four-year baccalaureate degree from a regionally accredited U.S. institution, or an equivalent degree from a non-U.S. institution.
  • Applicants must have earned a 3.0 GPA (on a 4.0 scale) in all prior undergraduate and graduate coursework.
  • Applicants must provide an official copy of transcripts for all of their post-secondary work.

 

General Requirements:

  • Statement of Purpose
  • Transcript(s)
  • TOEFL/IELTS/PTE (international graduate students)

 

Program-Specific Requirements:

  • Graduate Record Examination (GRE) (optional)
  • CV/Resume
  • Description of research/work experience
  • Prior coursework establishing quantitative ability (including calculus II, linear algebra, statistics, etc.)
  • Proficiency in programming languages, demonstrated either through prior programming coursework or substantial software development experience

The MS in AI is a 30-credit, 10-course, non-thesis graduate program designed for students to acquire the skills and knowledge necessary for a career in today’s information-based society.  

Sample Plan of Study (Full-time, three 3-credit courses per semester)

Semester 1 (fall)
  • MSAI601 Probability and Statistics
  • MSAI603 Principles of Machine Learning
  • MSAI631 AI and Society
Semester 2 (spring)
  • MSAI605 Computing Systems for AI
  • MSAI606 Human-Centered and Participatory Approaches to AI
  • MSAI630 Safe and Trustworthy AI
Semester 3 (summer)
  • Elective 1
Semester 4 (fall)
  • MSAI 602 Principles of Data Science
  • Elective 2
  • Elective 3

Sample Plan of Study (Part-time, two 3-credit courses per semester)

Semester 1 (fall)
  • MSAI601 Probability and Statistics
  • MSAI603 Principles of Machine Learning
Semester 2 (spring)
  • MSAI606 Human-Centered and Participatory Approaches to AI
  • MSAI605 Computing Systems for AI
Semester 3 (summer)
  • Elective 1
  • Elective 2
Semester 4 (fall)
  • MSAI602 Principles of Data Science
  • MSAI630 Safe and Trustworthy AI
Semester 5 (spring)
  • MSAI631 AI and Society
  • Elective 3

Electives Include: 

MSAI632 Generative AI
MSAI633 AI Policy
MSAI634 AI in Engineering
MSAI604 Introduction to Optimization for AI
MSAI612 Deep Learning for AI
MSAI641 Natural Language Processing for AI
MSAI642 Robotics for AI
MSAI650 Cloud Computing for AI
MSAI651 Big Data Analytics for AI

Learn more about the courses

Find up to date tuition and fee information here for the MS in Artificial Intelligence.

Program Directors & Instructors

Faculty Director, Master of Science in Data Science; Certificate in Data Science
Professor, Mathematics
Professor, Department of Electrical and Computer Engineering
Associate Director, Master's in Telecommunications Program, Electrical and Computer Engineering