Artificial Intelligence - Master of Science | College of Computer, Mathematical, and Natural Sciences

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.

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Admission Requirements

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

Sample Plan of Study & Courses

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
MSAI631 AI and Society

Semester 5 (spring)

MSAI630 Safe and Trustworthy AI
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

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Tuition & Fees

Up-to-date tuition and fee information for the MS in Artificial Intelligence.