SCHOOL OF TECHNOLOGY AND COMPUTING

Master of Science in Computer Science (MSCS)

Enrollment

All Quarters

Course Format

Online, On-Site (Seattle)

Total Credits

39-59

Advance Your Expertise in Technology

The Master of Science in Computer Science (MSCS) program enables students to broaden and build on abilities brought to the program to develop a broad base of competency and depth of study in the field of computer science beyond the undergraduate level. The program provides graduates with experiential learning opportunities to apply knowledge, tools, and techniques in real-world projects through an internship and a capstone project. 

Program Overview

Courses provide focus on programming, discrete math, data structures, algorithms, software engineering, cloud computing, artificial intelligence, machine learning, and full-stack development required to deliver Computer Science projects, as well as maintaining the professional skills needed to advance in the Computer Science field. Students will emerge with the experience and leadership identity required to influence the way that Computer Science is implemented and consumed in any corporation or government organization. 

The Depth of Study (DOS) sequence prepares students to demonstrate expertise in a specific area. The elective courses allow students to expand their interests in other disciplines. The internship provides students a vehicle to apply what they have learned in the degree to real work problems at a for-profit or a non-profit organization. 

The capstone is the platform that exhibits the synthesis of student’s academic accomplishments and experiential internships. Under the guidance of an advisor, the capstone can be a project, research paper, thesis or poster, and a public presentation designed to demonstrate mastery. 

Program Outcomes

The Master of Science in Computer Science will prepare students to:

Integrate a foundational knowledge of all areas of advanced computer science (General Computer Science Knowledge).

Apply fundamental principles and practices of advanced computer science (Computer Science Principles and Practices).

Apply critical and ethical thinking to solve problems in advanced computer science (Critical and Ethical Thinking).

Evaluate data to inform decisions and solve problems in advanced computer science (Quantitative Literacy).

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

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

Admission Requirements

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

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 SQL/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. 

Preparatory Courses (6 or 20 credits)

These preparatory courses may be required for students entering the MSCS degree program without sufficient related experience. 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 and Computing Components I
CS 11B Technology and Computing Components II

OR

Depth-First Preparatory Courses (20 Credits)

CS 132 Computer Science I *  OR  IS 201 Fundamentals of Computing
IS 360 Database Technologies *
CS 330 Network Communications *
CS 340 Operating Systems *

Core Requirements

Total Required Credits: 39 

Core Requirements (24 credits)

AI 510 Artificial Intelligence in Cloud Computing
AI 520 Natural Language Processing for Artificial Intelligence
CS 504 Software Engineering
CS 506 Programming for Computing
CS 519 Cloud Computing
CS 547 Secure Systems and Programs
CS 622 Discrete Math and Algorithms for Computing
DS 620 Machine Learning & Deep Learning

Depth of Study (6 Credits)

Depth of Study: Computer Science 
CS 624 Full-Stack Development –  Mobile App
CS 628 Full-Stack Development – Web Application

Elective (6 Credits) 

Students may select two elective courses from any graduate courses within the School of Technology & Computing OR complete the internship.

Internship

CS 680 Computer Science Internship * (3 credits)
This course is repeatable for credits.  Each enrollment must be pre-approved by the Program Manager.

Capstone (3 Credits)

CS 687 Computer Science Capstone *

Career Opportunities

Program Manager

Brian Maeng, Ph.D.
maengjooyol@cityu.edu

Upon graduating from CityU’s Master of Science in Computer Science (MSCS) program, you’ll be well-prepared for impactful careers at the intersection of computing and artificial intelligence. Our curriculum equips you for various roles, such as:

  • AI-Empowered Software Engineer: Develop intelligent software solutions by utilizing AI tools for faster development and integrating machine learning models directly into applications.
  • Full Stack AI Developer: Create comprehensive, end-to-end applications that seamlessly incorporate AI features, including intelligent user interfaces and smart backend systems.
  • AI Engineer: Focus on the design, development, and deployment of advanced AI and machine learning models, fostering innovation in fields like natural language processing, computer vision, and predictive analytics.
  • AI Systems Architect: Design and optimize scalable, resilient cloud and on-premise infrastructures essential for powering complex AI and machine learning systems.
  • Cloud AI Engineer: Deploy, manage, and scale AI workloads and services on leading cloud platforms, ensuring optimal performance and resource utilization.
  •  

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.

Click HERE for admissions and tuition information.

Click HERE for complete program catalog.

 

Updated: 6/17/2025