May 27, 2026  
Graduate Catalog | 2026-2027 
    
Graduate Catalog | 2026-2027

Artificial Intelligence, M.S.


The Master of Science in Artificial Intelligence program provides students with advanced skills and knowledge in planning, design, implementation, testing, and management of AI systems, applications, and infrastructures. Graduates with this degree will possess comprehensive training in core mathematics and AI algorithms, the AI software lifecycle, ethical considerations, as well as communication and teamwork abilities. The program features a wide selection of advanced courses that cover the latest developments in the ever-evolving field of AI. Students in the M.S. in Artificial Intelligence program are encouraged to utilize elective courses to explore additional disciplines, thereby enhancing their capabilities in creating practical AI solutions.

Admission Requirements


In addition to the general requirements for admission to the Graduate School, students applying for this program are expected to have knowledge of computer programming, data structures, calculus, statistics and linear algebra.  Students without undergraduate prerequisite courses in computer science and mathematics will be instructed to register for bridging coursework and demonstrate prior knowledge, as determined by the Graduate Program Director.

A bachelor’s degree in computer science would be beneficial. Individuals who have worked as professionals in the computer industry may be able to substitute work experience for some of the specific subject area admission requirements, subject to review by the Graduate Program Director.

Students must have an undergraduate grade point average of (or equivalent to) at least 3.0 (on a 4.0 point scale) and a Junior/Senior GPA of at least 3.0.

Student admission will be based on:

1. Prerequisites

a. Math Requirements (can be satisfied through bridging coursework):

  • Calculus
  • Linear Algebra and Statistics

b. Computer Science Requirements (equivalent work experience in relevant field will be considered and/or can be satisfied through bridging coursework):

  • Computer Programming
  • Data Structures

2. Undergraduate academic record

3. TOEFL, IELTS, and Duolingo (for international students)

4. GRE - Applicants who completed undergraduate degree outside of the United States may voluntarily submit GRE test scores and they will be reviewed as part of the holistic application consideration. Please note, the GRE requirement is optional.

5. Statement of purpose

6. Two positive letters of recommendation

Degree Requirements


Bridging Courses


Two intensive graduate-level courses designed to bridge a knowledge gap in a student’s background are offered. Students entering the program without the necessary programming or math background may need to take the bridging course appropriate for their background. These courses are not required for all students, but are designed to satisfy core prerequisites for students in the program. These courses may be counted as general electives.

Technical Courses (9 credit hours)


Select any three of the following (clusters are only suggestions):

General Elective Courses (6 credit hours)


Students select 6 credit hours of graduate-level courses that (1) do not have the ITAI course prefix and (2) are not ITIS 5270  or ITIS 5271 .  Students are encouraged to explore the courses from non-AI disciplines for learn and apply A.I. to solve interdisciplinary problems.

Capstone Course (3 credit hours)


Select one of the following courses. Credit hours from a capstone course may be counted towards a concentration requirement, too, if the same course is listed in that concentration. For students pursuing the M.S. Thesis, they will have to enroll in ITAI 6991  in two consecutive semesters (6 credit hours total), with the 3 credit hours satisfying the capstone requirement.

Degree Total = 30 Credit Hours


Grade Requirements


Core Courses must each be passed with A or B grades.  A minimum overall 3.0 GPA is required.