Artificial Intelligence Master of Science Degree
The artificial intelligence MS provides transferable skills in the responsible and impactful design, development, analysis, and deployment of AI.
Overview for Artificial Intelligence MS
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.
There is an enormous and growing demand for AI professionals across all sectors of society. This artificial intelligence master’s degree is designed for students with an interest in various AI sectors from various educational backgrounds.
You will develop well-rounded skill sets in designing, developing, and deploying AI systems, and also in understanding and analyzing AI’s impact on policy and society. A rich set of core courses prepares you with essential technical skills and knowledge.
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
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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.
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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.
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Affordable Now. Valuable for Life.
Earn your master’s degree without the full price tag. With Master Up you can receive a 30% tuition scholarship for an RIT master’s degree.
Careers and Cooperative Education
Typical Job Titles
| AI Engineer | Machine Learning Specialist | Software Developer |
| Entrepreneur | Research Associate | AI Policy Specialist |
| Technology Analyst | Computational Linguist |
Cooperative Education
What makes an RIT education exceptional? It’s the ability to complete relevant, hands-on career experience. At the graduate level, and paired with an advanced degree, cooperative education and internships give you the unparalleled credentials that truly set you apart. Learn more about graduate co-op and how it provides you with the career experience employers look for in their next top hires.
Cooperative education is optional but strongly encouraged for graduate students in the artificial intelligence master's degree.
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Curriculum for 2025-2026 for Artificial Intelligence MS
Current Students: See Curriculum Requirements
Artificial Intelligence MS
The curriculum below outlines the typical course sequence(s) for this program.
| First Year | ||
|---|---|---|
| Fall | Hours | |
| IDAI-610 | Fundamentals of Artificial Intelligence | 3 |
| IDAI-620 | Mathematical Methods for Artificial Intelligence | 3 |
| IDAI-700 | Ethics of Artificial Intelligence | 3 |
| Hours | 9 | |
| Spring | ||
| IDAI-710 | Fundamentals of Machine Learning | 3 |
| IDAI-720 | Research Methods for Artificial Intelligence | 3 |
| Elective | 3 | |
| Hours | 9 | |
| Second Year | ||
| Fall | ||
| Elective | 3 | |
| Elective | 3 | |
| Hours | 6 | |
| Spring | ||
| Select one of the following tracks: | 6 | |
| Professional Track: | ||
Elective | ||
| Capstone Project | ||
| Research Track: | ||
| Research & Thesis 1 | ||
| Hours | 6 | |
| Total Hours | 30 | |
Notes:
- IDAI-699 Graduate Co-op: A Co-Op is entirely optional at the graduate level, with permission of the school director, and may delay time to completion depending on scheduling constraints. Co-op experiences are zero credit.
- 1
IDAI-791 Continuation of Research and Thesis: An optional zero-credit course after completing IDAI-790 Research & Thesis.
Program Electives
| Code | Title | Hours |
|---|---|---|
| Independent Study | ||
| IDAI-799 | Independent Study in Artificial Intelligence | 1-3 |
| Machine Learning | ||
| CISC-863 | Statistical Machine Learning | 3 |
| CISC-865 | Deep Learning | 3 |
| or CMPE-679 | Deep Learning | |
| CSCI-736 | Neural Networks and Machine Learning | 3 |
| CSEC-720 | Deep Learning Security | 3 |
| DSCI-640 | Neural Networks | 3 |
| IMGS-789 | Graduate Special Topics (Topic ID # 20: Machine Learning for Difficult Data) | 3 |
| ISEE-601 | Systems Modeling and Optimization | 3 |
| ISEE-701 | Linear Programming | 3 |
| ISEE-702 | Integer and Nonlinear Programming | 3 |
| ISEE-761 | Forecasting Methods | 3 |
| MECE-689 | Grad.Lower Level Special Topic | 3 |
| STAT-747 | Principles of Statistical Data Mining | 3 |
| Natural Language and Speech Processing | ||
| PSYC-681 | Natural Language Processing and Large Language Models I | 3 |
| PSYC-682 | Natural Language Processing and Large Language Models II | 3 |
| PSYC-684 | Graduate Speech Processing | 3 |
| PSYC-712 | Graduate Cognition | 3 |
| Neuromorphic Computing | ||
| CMPE-755 | High Performance Architectures | 3 |
| CMPE-789 | Special Topics (Topic ID No. 30: Neuromorphic Computing) | 3 |
| COGS-610 | Laboratory Methods | 3 |
| COGS-760 | Foundations of Cognitive Modeling | 3 |
| CSCI-633 | Biologically Inspired Intelligent Systems | 3 |
| CSCI-722 | Data Analytics Cognitive Comp | 3 |
| Robotics | ||
| CSCI-632 | Mobile Robot Programming | 3 |
| EEEE-636 | Biorobotics/Cybernetics | 3 |
| EEEE-685 | Principles of Robotics | 3 |
| EEEE-784 | Advanced Robotics | 3 |
| Sociotechnical Analytics and Policy of Artificial Intelligence | ||
| COMM-717 | Artificial Intelligence and Communication | 3 |
| DSCI-633 | Foundations of Data Science and Analytics | 3 |
| ISTE-782 | Visual Analytics | 3 |
| MGIS-650 | Introduction to Data Analytics and Business Intelligence | 3 |
| PSYC-712 | Graduate Cognition | 3 |
| PSYC-714 | Graduate Engineering Psychology | 3 |
| PSYC-719 | Human Factors in Artificial Intelligence | 1-4 |
| PUBL-610 | Technological Innovation and Public Policy | 3 |
| PUBL-650 | AI, Policy and Law | 3 |
| Vision | ||
| CMPE-685 | Computer Vision | 3 |
| CMPE-789 | Special Topics (Topic ID No. 31 Robot Perception) | 3 |
| CSCI-731 | Advanced Computer Vision | 3 |
| CSCI-732 | Image Understanding | 3 |
| CSCI-736 | Neural Networks and Machine Learning | 3 |
| EEEE-670 | Pattern Recognition | 3 |
| IMGS-621 | Computer Vision | 2 |
| IMGS-682 | Image Processing and Computer Vision | 3 |
| IMGS-712 | Multi-view Imaging | 3 |
| IMGS-789 | Graduate Special Topics (Topic ID No. 10 Deep Learning for Vision ) | 1-3 |
| IMGS-789 | Graduate Special Topics (Topic ID No. 19 Robust Machine Learning for Interdisciplinary Imaging Science Applications) | 1-3 |
| PSYC-715 | Graduate Perception | 3 |
| Other | ||
| CMPE-757 | Quantum Computing | 3 |
| DSCI-650 | High Performance Data Science | 3 |
| MATH-689 | Advanced Special Topics (Topic ID No. 3 Mathematical Data Science) | 1-4 |
| SWEN-601 | Software Construction | 3 |
| SWEN-711 | Engineering Self-Adaptive Software Systems With Reinforcement Learning | 3 |
Note for online students
The frequency of required and elective course offerings in the online program will vary, semester by semester, and will not always match the information presented here. Online students are advised to seek guidance from the listed program contact when developing their individual program course schedule.
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Admissions and Financial Aid
This program is available on-campus or online.
On Campus
| Offered | Admit Term(s) | Application Deadline | STEM Designated |
|---|---|---|---|
| Full-time | Fall | Rolling | Yes |
| Part-time | Fall | Rolling | No |
Online
| Offered | Admit Term(s) | Application Deadline | STEM Designated |
|---|---|---|---|
| Part-time | Fall | Rolling | No |
Full-time study is 9+ semester credit hours. Part-time study is 1‑8 semester credit hours. International students requiring a visa to study at the RIT Rochester campus must study full‑time.
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 2026 applicants. No minimum score requirement.
- Submit English language test scores (TOEFL, IELTS, PTE Academic, etc.), if required. Details are below.
English Language Test Scores
International applicants whose native language is not English must submit one of the following official English language test scores. Some international applicants may be considered for an English test requirement waiver.
Duolingo (DET): 130
IELTS: 6.5
PTE Academic: 60
TOEFL: 88
International students below the minimum requirement may be considered for conditional admission. Deaf and hard-of-hearing test takers with significant hearing loss do not need to take the listening and speaking sections for the TOEFL and IELTS. Each program requires balanced sub-scores when determining an applicant’s need for additional English language courses.
How to Apply Start or Manage Your Application
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
Additional Information
Prerequisites
Applicant must have college-level credit in Python programming and mathematics.
Online Degree Information
The online MS in artificial intelligence program offers core courses online in an asynchronous modality. Bridge courses, when assigned, are also taught asynchronously. Any live class or group meetings are usually optional in bridge and core courses. Elective courses for the online program are more limited than courses in the on-campus program and their availability will vary from semester to semester. Some electives will be synchronous only. Students in the online program have access to RIT computing and library resources. The online program is part-time, with students completing 1-2 courses per semester. Students will usually spend 10-12 hours per week per class, although this depends on course content and individual background knowledge. For details about the online learning experience, contact the program contact listed on this page. RIT does not offer international student visas for online study.
Online Tuition Eligibility
The online MS in artificial intelligence is a designated online degree program billed at a discount from the on-campus rate. Additional scholarships are not offered. View the current online tuition rate.
Online Study Restrictions for Some International Students
Certain countries are subject to comprehensive embargoes under US Export Controls, which prohibit virtually ALL exports, imports, and other transactions without a license or other US Government authorization. Learners from the Crimea region of the Ukraine, Cuba, Iran, North Korea, and Syria may not register for RIT online courses. Nor may individuals on the United States Treasury Department’s list of Specially Designated Nationals or the United States Commerce Department’s table of Deny Orders. By registering for RIT online courses, you represent and warrant that you are not located in, under the control of, or a national or resident of any such country or on any such list.
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