The MS in Artificial Intelligence (MS-AI) prepares students to lead in a field reshaping education, computing, energy, data analysis, information systems, and nearly every sector of the modern economy. Designed for students seeking to go beyond a general computing degree, the program offers a focused, rigorous pathway into AI research, development, and deployment, equipping graduates to drive innovation across industry, government, and academia.
As an R-1 (Very High Research Activity) institution under the Carnegie classification, UMBC supports a faculty at the forefront of AI innovation. CSEE faculty publish in top-tier venues (NeurIPS, ICML, ACL, EMNLP, AAAI, IEEE TPAMI, and others), lead federally funded research programs through agencies including NSF, NIH, DARPA, and ONR, and direct nationally recognized centers in Artificial Intelligence, cybersecurity, and quantum science. Students in the MS-AI program gain direct access to this ecosystem, through advanced coursework, research assistantships, capstone projects with faculty PIs, and collaboration with active AI faculty whose work spans foundation models, trustworthy and interpretable AI, clinical and mental health NLP, multimodal learning, robotics, AI for science, and others.
Requirements
The requirements for the M.S. degree are summarized as follows.
- 24 credits of graduate coursework plus six credits of CMSC 799 (thesis option) or 33 credits of graduate coursework (non-thesis option).
- Completion of two “core” classes, in which a grade of a B or better must be earned, and three electives from Bucket A.
- The thesis must be supervised by an approved CSEE graduate faculty member as the thesis advisor and must, upon completion of the research, be defended with an oral presentation and accepted by the student’s M.S. thesis committee.
- Certain restrictions apply:
- A minimum overall GPA of 3.0 is required to graduate
- Completing the program within a maximum of five years
- Completing each of the milestones according to the timeline specified below
Qualifying Courses
Core Courses
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Electives: Bucket A
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Electives: Bucket B
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CMSC 799 – Master’s Thesis ResearchThe CMSC 799 MS Thesis Research component at University of Maryland, Baltimore County provides students with the opportunity to engage directly in cutting-edge AI research under faculty mentorship. UMBC’s AI faculty span a wide range of domains, including natural language processing, knowledge graphs, computer vision, explainable AI, cybersecurity, human-centered AI, and healthcare applications. Faculty-led research groups and labs actively address real-world challenges such as trustworthy AI systems, causal inference, cyber-physical security, and data-driven decision-making, reflecting a deeply interdisciplinary and application-oriented research culture. With more than 50–65 faculty engaged in AI and related areas across multiple departments and research centers, students in CMSC 799 are embedded within a mature and collaborative research ecosystem that supports both foundational advances and translational impact. Prospective students are encouraged to explore the breadth of faculty expertise and identify potential research mentors through the AI faculty directory. Additionally, MS in AI encourages students to take some number of electives outside CMSC for their degree. |
Learning Outcomes
Upon completion of the MS-AI degree, students will be able to begin successful careers in research, academia, and industry. The MS-AI program responds to the rapidly growing field of AI technology. Graduates can pursue careers in technology, finance, national defense, cybersecurity, healthcare, government, or research. The table below lists some potential job roles and responsibilities. Such as AI Engineer / Machine Learning Engineer, Data Scientist (AI Specialization), Research Scientist (AI/ML), AI Product Manager, Computer Vision Engineer.
Students completing the MS in AI will be expected to
- Acquire a deep understanding of core AI principles, including search algorithms, reasoning, and learning, through Principles of Artificial Intelligence (CMSC 671) and Machine Learning (CMSC 678).
- Expand their expertise by selecting electives from Bucket A, covering computer vision, natural language processing, neural networks, and robotics, equipping them with the necessary knowledge to work on specialized AI applications.
- Develop strong computational abilities through electives in Bucket B in data visualization, algorithm design, numerical computation, symbolic processing, and multi-agent systems, enabling them to solve complex AI-related problems.
- Thesis Track: Conduct independent research (CMSC 799), exploring advanced AI methodologies, designing experiments, and contributing to the field through novel findings and technical publications.
- Non-Thesis Track: Complete additional coursework and may participate in independent studies or internships, preparing them for AI-driven roles in industry and applied research.
- Stay updated on emerging AI trends and deepen their technical knowledge in areas of personal or professional interest through special topics courses, such as Neurosymbolic Artificial Intelligence (CMSC 691) and independent study opportunities (CMSC 696, CMSC 699).
Admissions
- Admissions are offered only for Fall and Spring semesters.
- 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
- GRE scores are not required.
- 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.
Application Process
Apply online through UMBC’s Graduate School Website. Applicants must also submit:
- An Official Transcript
- Two letters of recommendation
- Statement of purpose
Application Deadlines
NEW: Application fee WAIVED for applicants who apply from May 27 to June 03 2026. See campaign here.
International Students
- Fall: January 20th
- Spring: June 1st
Domestic Students
- Fall: January 20th (for graduate assistantship consideration), August 1st
- Spring: June 1st (for graduate assistantship consideration), November 1st
Program Contact
For more information about the MS in AI program, contact Dmitri Perkins.
Dmitri Perkins
Graduate Program Director, CSEE
Office: 350 Information Technology and Engineering (ITE) Building,
Email: dmitrip1@umbc.edu
Phone: (410) 455-3019
Note: Before contacting the program, please review the Frequently Asked Questions (FAQ) section.