M.S. in Computer Science

The M.S. in Computer Science is a research-intensive program designed for computer scientists ready to tackle harder problems, advancing their mastery of theory, systems, and emerging specializations that define the frontier of the field. Building on students' existing CS foundations, the curriculum dives deep into advanced algorithms, theoretical computer science, and emerging programming paradigms, developing the rigorous analytical thinking required for senior R&D roles and Ph.D. programs. Electives in operating systems, mobile computing, computer graphics, DevOps, human-computer interaction, and software system security allow students to tailor the degree to their interests, whether that's building scalable cloud-native systems, developing secure applications, or creating immersive AR/VR experiences. Throughout, the curriculum reflects how modern software engineering is evolving: courses integrate AI-augmented development practices, including LLM-powered coding agents, automated CI/CD pipelines, and AI-assisted security tools that are rapidly becoming standard in industry R&D environments.

For students drawn to AI, the program's elective offerings in machine learning, neural networks and deep learning, and AI provide a direct path into the most consequential computing specialization of our time, covering everything from GPU-accelerated deep learning architectures and transformer-based models to reinforcement learning, agentic AI systems, and vision-language models. The program culminates in a two-part capstone that mirrors real-world engineering and research execution: students define a problem, scope requirements, build toward a production-quality deliverable, and present their work to faculty and peers. The result is a portfolio-ready project that demonstrates the end-to-end capability, from system design through rigorous evaluation and clear communication, that top employers and Ph.D. programs expect.

The 10-course (30-credit) M.S. in Computer Science can be completed full time in 1.5 years, or part time at a pace that makes sense for you. View a typical full-time course sequence, review degree requirements, and download course descriptions below. 

Sample Full-Time Course Sequence

Course Descriptions

No computer science background? The M.S. in Computer Science — Agile is for you. This pathway builds rigorous, industry-ready computer scientists from the ground up, starting with a five-course foundational sequence in programming, algorithms, data structures, and computer systems architecture before advancing into the same advanced curriculum, electives, AI specializations, and capstone experience as the standard track. 

Degree Requirements

Advanced CS Core (3 courses / 9 credits)

• COM 5100 Advanced Algorithms
• COM 5101 Theoretical Computer Science and its Applications
• COM 5102 Emerging Paradigms in Programming

Electives (6 courses / 18 credits)*

• AIM 5006 Artificial Intelligence
• AIM 5001 Data Acquisition & Management
• AIM 5005 Machine Learning
• AIM 5007 Neural Network and Deep Learning
• AIM 5002 Computational Statistics and Probability
• COM 5110 Operating Systems
• COM 5222 Fundamentals of Software Engineering
• COM 5323 Computer Graphics
• COM 5421 DevOps
• COM 5210 Mobile Computing and Apps Development
• COM 5120 Human-Computer Interaction
• COM 5440 Software System Security
• COM 5441 Hardware Security
• COM 5014 Special Topics (1-3 cr.)
• COM 5550 Internship (1-3 cr.)
• COM 5999 Independent Study (1-3 cr.)

Capstone (3 credits)

• COM 6000 Capstone in Comp Sci 1 (1.5 cr.)
• COM 6001 Capstone in Comp Sci 2 (1.5 cr.) 

*Electives: At least 12 credits must be from COM or AIM; additional elective courses may be selected from any graduate department at YU or elsewhere with permission of the program director. Offerings vary each semester. Therefore, some choices will not be available for a particular cohort. Internship can be taken as an elective beginning in the summer semester.

All courses are three credits unless otherwise noted.