Masters+

Ph.D.+

Why Study Artificial Intelligence?

The MS in Artificial Intelligence (MS-AI) prepares students to lead in AI research, development, and deployment. This program serves students seeking a focused pathway beyond a general computing degree. It offers access to federally funded research programs through agencies like NSF, NIH, and DARPA.

Students in the MS-AI program study core AI principles, including search algorithms, reasoning, and learning. They also explore subfields such as computer vision, natural language processing, neural networks, and robotics. This diverse curriculum connects foundational knowledge with specialized applications. Graduates leave the program equipped to tackle complex AI-related problems.

The program offers two tracks: a thesis track and a non-thesis track. The thesis track involves conducting independent research through CMSC 799, allowing students to explore advanced AI methodologies. The non-thesis track focuses on additional coursework and may include independent studies or internships. Both tracks prepare students for careers in industry, academia, or research.

At a Glance

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FINANCIAL AID ↓HOW TO APPLY ↓APPLICATION DEADLINES ↓PROGRAM REQUIREMENTS ↓PROGRAM CONTACTS ↓

Is Artificial Intelligence the Right Master's Degree for You?

UMBC is an R-1 institution with over 50-65 faculty engaged in AI research across various domains. Faculty lead projects funded by agencies like NSF, NIH, and DARPA, focusing on areas such as trustworthy AI, causal inference, and cyber-physical security. This environment fosters collaboration and real-world problem-solving. Students can engage with nationally recognized centers in AI, cybersecurity, and quantum science.

Access to faculty-led research groups and labs enhances student outcomes. Students can participate in capstone projects and research assistantships, gaining hands-on experience in AI applications. This involvement prepares them for successful careers as AI engineers, data scientists, or research scientists. The program’s collaborative culture supports both foundational and translational research.

How Will You Gain Experience?

Thesis Research

Students in the thesis track engage in CMSC 799, conducting independent research under faculty mentorship. They explore advanced AI methodologies and design experiments to contribute novel findings to the field. This experience develops their research skills and prepares them for technical publications. Graduates leave with a strong foundation in AI research.

Capstone Projects

Students collaborate with faculty PIs on capstone projects, applying their knowledge to real-world challenges. These projects often focus on areas like trustworthy AI systems or data-driven decision-making. This hands-on experience enhances their problem-solving abilities and prepares them for industry roles. Students gain valuable insights into practical applications of AI.

Research Assistantships

Through research assistantships, students work alongside faculty in active AI labs. They participate in projects funded by agencies like NSF and NIH, gaining exposure to cutting-edge research. This experience helps students develop technical skills and professional networks. It also prepares them for future careers in academia or industry.

You might like this program if you’re interested in skills like:

ai
AI ethics
AI systems
artificial intelligence
assistive technology

What Classes Can You Take?

The MS-AI curriculum is built around two required core courses in AI principles and machine learning, with students selecting additional electives from a curated set of specialized and supporting topics. Elective offerings span computer vision, natural language processing, neural networks, robotics, and a wide range of computational and domain-specific areas, giving students the flexibility to tailor their degree to their research and career goals.

Featured Courses

CMSC 671 - Principles of Artificial Intelligence

This course covers core AI principles, including search algorithms, reasoning, and learning.

CMSC 678 - Introduction to Machine Learning

Students learn foundational concepts and techniques in machine learning, preparing them for advanced applications.

CMSC 672 - Computer Vision

This course explores techniques for enabling computers to interpret and understand visual information.

CMSC 673 - Introduction to Natural Language Processing

Students study methods for processing and analyzing human language data.

CMSC 675 - Introduction to Neural Networks

This course introduces students to the principles and applications of neural networks in AI.

Tuition, Scholarships & Financial Aid

Find opportunities to further advance your career and academic studies.

UMBC participates in all federal and state student financial aid programs and offers scholarships and assistantships through the Graduate School, Graduate Departments and the Office of Financial Aid and Scholarships.

2025–2026 Graduate Cost Calculator Graduate Assistantships Fellowships Funding Your Education

Ready to Apply?

Review Master of Science in Artificial Intelligence Requirements

Applicants must hold a four-year bachelor’s degree from:

A regionally accredited U.S. institution, or
An equivalent non-U.S. university.

A minimum cumulative GPA of 3.0 (on a 4.0 scale) is desired across all prior undergraduate and graduate studies.

International applicants must provide:

Proof of English proficiency
Financial certification
Appropriate visa documentation
A narrative statement is required, covering:
- Academic and professional background
- Areas of interest

English proficiency exams (e.g., TOEFL or equivalent) are required if:

The applicant does not hold a degree from a U.S. institution, or
Prior instruction was not conducted in English

The University of Maryland, Baltimore County Graduate School and the MS-AI Admissions Committee jointly make the final admission decision.
Maryland residency is not required for enrollment.
As part of the University System of Maryland, Maryland residents qualify for a reduced in-state tuition rate.

Start Your Graduate Admissions Application

Please note that application decisions can take 6-8 weeks after the program’s deadline, and depend on how many applications a department receives. You will receive an email once the department processes your decision letter. You will be able to see your decision letter by logging in to the application website. Your decision letter will be where the application checklist was. You may also check your recommendation statuses to send reminders or update contact information from the user page. If you are having trouble logging back in, you can recover your account.

Have Questions?

Please contact the appropriate Graduate School staff member for assistance, or contact our Main Office at gradschool@umbc.edu or 410-455-2537.

Application Deadlines

Fall 2026 Application Deadlines are extended to August 1, 2026 for this program

Spring Semester

International Students:
Apply by June 1

Domestic Students:
Apply by November 1

Fall Semester

International Students:
Apply by January 20

Domestic Students:
Apply by June 1

UMBC Graduate School Application UMBC Grad School Admissions Info UMBC Grad School Required Documents

Contact Information

Artificial Intelligence Program Contacts

Program Director

Dmitri Perkins
(410) 455-3019
dmitrip1@umbc.edu

UMBC Graduate School Admissions Office Contact Information

Mailing Address

UMBC Graduate School
1000 Hilltop Circle Baltimore, MD 21250

Admissions Staff

Staff are available from
Mon - Fri, 9 a.m. to 5 p.m. 410-455-2537

Request Help

Email Graduate Admissions at gradschool@umbc.edu.

Master of Science in Artificial Intelligence