Master of Science in Artificial Intelligence


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Course Format


Total Credits


Lead Innovations With AI

The Master of Science in Artificial Intelligence (MSAI) is designed to prepare graduates with the foundations, principles, and technical knowledge, to master the comprehensive framework of theory and practice in the emerging field of AI. Students will gain technical skills and practical expertise for developing and deploying artificial intelligence techniques to real-world applications.

Program Overview

The MSAI program will allow students to gain an understanding of AI technology, its applications, and its use cases. The program consists of the core requirements, the depth of study, a choice of courses, and the capstone. Core requirements include fundamental concepts, techniques, tools, and practices related to artificial intelligence such as machine learning, deep learning, MLOps, and natural language processing. In addition to the core courses, the Depth of Study sequence prepares students to demonstrate expertise in artificial intelligence with courses such as Agent Based Systems, and Emerging Topics in Artificial Intelligence.

A choice of courses allows students to expand their interests in other disciplines, such as Computer Science, Cybersecurity, or Data Science. Students can select an internship as an option. Students complete the capstone course which can be a project, research paper, thesis, poster, or a public presentation designed to demonstrate mastery.

Learning Outcomes

The Master of Science in Artificial Intelligence will prepare students to:

Apply foundational knowledge, principles, and practices of artificial intelligence (General Artificial Intelligence Knowledge).

Implement artificial intelligence principles and applied practices to use cases (Artificial Intelligence Principles and Practices).

Analyze critical and ethical thinking to solve problems in artificial intelligence (Critical and Ethical Thinking).

Evaluate data to inform decisions and solve problems in artificial intelligence (Quantitative Literacy).

Create the ability to develop and express ideas while applying a variety of delivery modes, genres, and communication styles (Communication).

Collaborate effectively on diverse teams to accomplish a common goal (Collaboration).


Admissions Requirement

A bachelor’s degree from an accredited university is required to enroll in this program.

A bachelor’s degree from an accredited university is required to enroll in this program. The School of Technology and Computing encourages students with a non-technical bachelor’s degree to pursue the MSAI. Preparatory courses for the degree include:

Breadth-First Preparatory Courses (6 Credits)

CS 11A Technology and Computing Components I

CS 11B Technology and Computing Components II

Depth-First Preparatory Courses (20 Credits)

CS 132 Computer Science I 

CS 330 Network Communications

CS 340 Operating Systems

IS 360 Database Technologies


Total Required Credits: 39 

Pre-Entry Requirement (0 Credits)
CS 500 STC MS Orientation to Master’s Programs
Core Requirements (24 Credits)
AI 500    Artificial Intelligence Overview
AI 510    Artificial Intelligence in Cloud Computing
AI 520    Natural Language Processing for Artificial Intelligence
CS 506   Programming for Computing
CS 622   Discrete Math and Algorithms for Computing
DS 510  Artificial Intelligence for Data Science
DS 620  Machine Learning & Deep Learning
DS 623  Math & Statistics for Data Science
Depth of Study (6 Credits)
AI 610    Agent Based Systems
AI 620    Emerging Topics in Artificial Intelligence
Elective (6 Credits)

Students may select two electives from any graduate courses within the School of Technology & Computing or complete the internship after taking three CS 650 seminar courses for their internship preparation.


AI 680 Artificial Intelligence Internship (repeatable)

Capstone (3 Credits) 

AI 687 Artificial Intelligence Capstone

Career Opportunities

Program Manager

Sion Yoon, Ph.D.

Enterprise applications for AI are growing, fueling the demand for AI experts. In 2019, Gartner surveyed organizations in 89 countries and found in the last four years, there was a 270% jump in artificial intelligence implementation. With the increased adoption of AI in industries, there is a high demand for AI skills.

MSAI prepares graduates for high-demand careers such as AI Engineer, Machine Learning Engineer, MLOps Engineer, Software Development Engineer, AI Engineering Manager, and AI Project Manager.

Click HERE for admissions and tuition information.

Click HERE for the complete program catalog.

Updated: 8/31/2023