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Master of Science in Artificial Intelligence

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 Information Summary

Enrollment: All Quarters

Course Format: Online

Total Credits: 39-59

Program Manager

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Dr. Sherin Aly
alysherin@cityu.edu

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The Master of Science in Artificial Intelligence curriculum is designed to prepare graduates with the foundation, 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 ethical and human-centered artificial intelligence techniques to real-world applications.

The core courses provide comprehensive foundations and practical applications. Students take courses in AI programming, discrete math and algorithms, machine learning and deep learning, natural language processing, agent-based systems, cloud computing, among other courses, and cover special topics before the applied capstone project that simulates real-world experience.

Click HERE for admissions and tuition information.

Click HERE for the complete program catalog.

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).

Note: For full course descriptions please refer to the current catalog.

Admission Requirements

In addition to City University of Seattle’s graduate admission requirements, found under Admissions in the catalog menu, applicants to this program must also meet the following requirements:

An earned bachelor’s degree and evidence of completion of undergraduate courses or their equivalent in:

  • Equivalency of 5-quarter hour credits at the intermediate level in at least one computer programming language; and
  • Equivalency of 5-quarter hour credits in networking (TCP/IP from physical through applications layers); and
  • Equivalency of 5-quarter hour credits of data management including basic database design and SOL/NoSQL Queries; and
  • Equivalency of 5-quarter hour credits of operating systems including OS theory, process management, and memory management; OR

An earned bachelor’s degree and successful completion of CityU’s Undergraduate Certificate in Foundations of Systems Development.

Total Required Credits (39-59 Credits)

Preparatory Courses (6 or 20 Credits)

Preparatory courses may be required for students entering the MSAI degree program without sufficient related experience in programming, SQL/NO SQL databases, networking, and operating systems. The breadth-first preparatory courses are recommended for students who want to study a broad spectrum of all topics within 1 quarter. The depth-first preparatory courses are recommended for students who want to study each topic in depth. Please see the program admissions criteria in the City University of Seattle catalog for specific information.

Breadth-First Preparatory Courses (6 Credits)

CS 11A   Technology & Computing Components I

   3

CS 11B   Technology & Computing Components II

   3

Depth-First Preparatory Courses (20 Credits)

IS 201   Fundamentals of Computing

   5

IS 360   Database Technologies *

   5

CS 340   Operating Systems *

   5

CS 330   Network Communications *

   5

Major in Artificial Intelligence (30 Credits)

AI 500   Artificial Intelligence

   3

AI 510   Artificial Intelligence in Cloud Computing

   3

AI 520   Natural Language Processing for Artificial Intelligence

   3

CS 506   Programming for Computing

   3

DS 620   Machine Learning & Deep Learning

   3

CS 622   Discrete Math and Algorithms for Computing

   3

CS 519   Cloud Computing

   3

DS 623   Math & Statistics for Data Science

   3

AI 610   Agent Based Systems

   3

AI 620   Emerging Topics in Artificial Intelligence

   3

Electives (6 Credits)

Students may select two electives from any graduate courses within the School of Technology & Computing.

Capstone (3 Credits)

AI 687   Artificial Intelligence Capstone *

   3

Courses with an asterisk (*) after their title have a pre- or co-requisite.

According to ExplodingTopics‘ data, 78 % of companies have now been embedding AI into their business models. With many of them planning to expand that investment over the next three years, the market for professionals who can build, deploy, and govern intelligent systems has never been stronger. Graduates of CityU’s Master of Science in Artificial Intelligence (MSAI) are prepared to excel in roles such as:

  • Machine-Learning Engineer: Design, train, and fine-tune supervised, unsupervised, and deep-learning models for recommender systems, computer vision, and NLP.
  • MLOps / AI Platform Engineer: Automate model versioning, CI/CD pipelines, and scalable inference on AWS, Azure, or GCP, ensuring reliable, secure production AI.
  • AI Software Engineer: Integrate pre-built and custom models into full-stack applications, delivering intelligent user experiences from front end to back end.
  • AI Systems Architect: Plan fault-tolerant data pipelines, real-time model-serving layers, and security controls for enterprise-scale AI workloads.
  • Responsible-AI & Ethics Specialist: Assess bias, privacy, and compliance risks; implement governance frameworks that keep AI trustworthy and regulation-ready.
  • AI Product Manager: Translate business goals into model requirements and guide cross-functional teams from prototype to market launch.

Our graduates consistently secure positions at the forefront of innovation, with alumni contributing to renowned companies such as Adobe, AWS, Google, Meta, and Microsoft, among others. They apply their skills to transform various industries, including healthcare (AI diagnostics), manufacturing (predictive maintenance), education (personalized learning AI), finance (algorithmic trading), green energy (smart grid optimization), and the broader technology sector, where they drive the next wave of innovation.