Program Overview

Artificial Intelligence Master of Science Degree

Overview

The artificial intelligence MS provides transferable skills in the responsible and impactful design, development, analysis, and deployment of AI.

Why Pursue a Master's in Artificial Intelligence at RIT?

• STEM-OPT Visa Eligible: The STEM Optional Practical Training (OPT) program allows full-time, on-campus international students on an F-1 student visa to stay and work in the U.S. for up to three years after graduation.
• Flexible Learning: Complete your degree entirely online, or via a combination of online and traditional on-campus courses.
• AWARE-AI Program: MS in AI students have the opportunity to become National Science Foundation’s AWARE-AI trainees and experience AI research carefully curated with career-enhancing activities.

AI Master’s Program

RIT’s artificial intelligence master’s offers you a tailored experience through your choice of electives. For example, you can study a central AI topic or an impactful domain of AI applications. You will gain career-enhancing experience through hands-on projects and course work. Prior to graduation, a capstone or an optional thesis allows you apply learned skills to evaluate or investigate an active area in artificial intelligence.

AI Curriculum

• Core courses: You will develop a range of essential AI skills and knowledge through core courses. If necessary, there are computer programming and a mathematical bridge course available.
• Elective courses: Make this degree your own by customizing electives to fit your goals. Develop depth in an area of special interest with electives that focus on central AI themes such as machine learning, natural language and speech processing, computer vision, robotics, sociotechnical AI analysis, and more.
• Capstone or thesis: Choose to complete a capstone course and an extra elective course or spend the equivalent of two courses on a thesis project with an individual expert advisor.

Interdisciplinary AI Curriculum

The graduate program in artificial intelligence is jointly delivered by faculty experts from four RIT colleges–Golisano College of Computing and Information Sciences, College of Liberal Arts, College of Science, and Kate Gleason College of Engineering–allowing you to grow valuable, career-enhancing interdisciplinary skills and communication competency as part of your program experience.

Careers in Artificial Intelligence

Graduates of the artificial intelligence MS are equipped with the tools and knowledge for successful careers in industry or other organizations. They will also be prepared for doctoral degree programs in a range of areas, as the impact of AI expands into established and emerging career professions.

Curriculum for Artificial Intelligence MS

Artificial Intelligence, MS degree, typical course sequence

• First Year:
  • IDAI-610: Fundamentals of Artificial Intelligence
  • IDAI-620: Mathematical Methods for Artificial Intelligence
  • IDAI-700: Ethics of Artificial Intelligence
  • IDAI-710: Fundamentals of Machine Learning
  • IDAI-720: Research Methods for Artificial Intelligence
  • Program Elective
• Second Year:
  • Choose one of the following tracks:
    • IDAI-780: Capstone Project, plus one additional Program Elective
    • IDAI-790: Research and Thesis
  • Program Electives

MS Program Electives

Machine Learning

• CISC-863: Statistical Machine Learning
• CMPE-679: Deep Learning
• CISC-865: Deep Learning
• CSCI-736: Neural Networks and Machine Learning
• DSCI-640: Neural Networks
• ISEE-601: Systems Modeling and Optimization
• ISEE-701: Linear Programming
• ISEE-702: Integer and Nonlinear Programming
• ISEE-761: Forecasting Methods
• MECE-689: Grad. Lower Level Special Topic: Reinforcement Learning
• STAT-747: Principles of Statistical Data Mining

Natural Language and Speech Processing

• PSYC-681: Natural Language Processing I
• PSYC-682: Natural Language Processing II
• PSYC-684: Graduate Speech Processing

Neuromorphic Computing

• CMPE-755: High Performance Architectures
• CMPE-789: Special Topics (Topic ID #30 Neuromorphic Computing)
• COGS-610: Laboratory Methods
• COGS-760: Foundations of Cognitive Modeling
• CSCI-633: Biologically Inspired Intelligent Systems
• CSCI-722: Data Analytics Cognitive Comp

Robotics

• CSCI-632: Mobile Robot Programming
• EEEE-636: BioRobotics/Cybernetics
• EEEE-685: Principles of Robotics
• EEEE-784: Advanced Robotics

Sociotechnical Analytics and Policy of Artificial Intelligence

• COMM-717: Artificial Intelligence and Communication
• DSCI-633: Foundations of Data Science and Analytics
• ISTE-782: Visual Analytics
• MGIS-650: Introduction to Data Analytics and Business Intelligence
• PSYC-712: Graduate Cognition
• PSYC-714: Graduate Engineering Psychology
• PSYC-719: Human Factors in Artificial Intelligence
• PUBL-610: Technological Innovation and Public Policy
• PUBL-650: AI, Policy and Law

Vision

• CMPE-685: Computer Vision
• CSCI-731: Advanced Computer Vision
• CSCI-732: Image Understanding
• CSCI-736: Neural Networks and Machine Learning
• EEEE-670: Pattern Recognition
• IMGS-612: Computer Vision
• IMGS-682: Image Processing and Computer Vision
• IMGS-712: Multi-view Imaging
• IMGS-789: Graduate Special Topics (Topic ID #10 Deep Learning for Vision)
• IMGS-789: Graduate Special Topics (Topic ID #19 Robust ML Interdisciplinary Imaging Science App)
• PSYC-715: Graduate Perception

Other

• DSCI-650: High Performance Data Science
• SWEN-601: Software Construction
• SWEN-711: Engineering Self-Adaptive Software Systems With Reinforcement Learning
• IDAI-799: Independent Study in Artificial Intelligence

Admissions and Financial Aid

Application Details

To be considered for admission to the Artificial Intelligence MS program, candidates must fulfill the following requirements:

• Complete an online graduate application.
• Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned.
• Hold a baccalaureate degree (or US equivalent) from an accredited university or college. A minimum cumulative GPA of 3.0 (or equivalent) is recommended.
• Satisfy prerequisite requirements and/or complete bridge courses prior to starting program coursework.
• Submit a current resume or curriculum vitae.
• Submit a personal statement of educational objectives.
• Submit two letters of recommendation.
• Entrance exam requirements: GRE optional for Fall 2025 applicants. No minimum score requirement.
• Submit English language test scores (TOEFL, IELTS, PTE Academic), if required.

Cost and Financial Aid

An RIT graduate degree is an investment with lifelong returns. Graduate tuition varies by degree, the number of credits taken per semester, and delivery method. View the general cost of attendance or estimate the cost of your graduate degree.

A combination of sources can help fund your graduate degree. Learn how to fund your degree.

Faculty

• Zhiqiang Tao
• Zachary Butler
• Ernest Fokoue

Facilities

• Multi-Agent Bio-Robotics Laboratory
• Adaptive Human-Robot Teaming Lab
• Brain Lab

Resources

Current students in the artificial intelligence master’s program may refer to these resources for additional information.

Related News

• April 28, 2025: Trump Executive Order Sets Stage for AI Revolution in Higher Education
• February 21, 2025: RIT joins statewide Empire AI consortium
• February 10, 2025: Eva Navarro among list of 100 Brilliant Women in AI Ethics 2025