Computer Science, Master of Science
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 experience in acquiring and applying knowledge, tools, and techniques to significant projects and studies through real-world experiences through either a repeatable internship or a capstone project.
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 Choice 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 internship learnings. 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 Computing 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
In addition to City University of Seattle's graduate admission requirements, found under Admissions in the catalog menu, students enrolling in the School of Technology and Computing graduate programs must meet the requirements listed below:
- An earned Bachelor of Arts or a Bachelor of Science degree in Information Technology or Computing-related majors such as Computer Systems, Computer Science, Information Systems, Information Technology, Cybersecurity; OR
- An earned Bachelor's degree in another field 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 credits of data management including basic database design and SOL/NoSQL Queries; and
- Equivalency of 5-quarter credits of operating systems including OS theory, process management, and memory management; OR
- An earned Bachelor's degree in another field and successful completion of CityU’s Undergraduate Certificate in Foundations of Systems Development.
Total Required Credits (39-59 Credits)*
*Preparatory courses may be required for students entering the MS - Computer Science degree program without sufficient related experience. Please see the program admissions criteria in the City University of Seattle catalog for specific information.
Preparatory Courses (20 Credits)
Core Requirements (24 Credits)
| CS 504 | Software Engineering | 3 |
| CS 506 | Programming for Computing | 3 |
| CS 519 | Cloud Computing Overview | 3 |
| CS 533 | Computer Architecture | 3 |
| CS 547 | Secure Systems and Programs | 3 |
| CS 622 | Discrete Math and Algorithms for Computing | 3 |
| DS 510 | Artificial Intelligence for Data Science | 3 |
| DS 620 | Machine Learning & Deep Learning | 3 |
Choice Coursework (6 Credits Graduate Level)
| Choose two courses from those listed below | |
| CS 680 | Computer Science Internship | 3 |
| DS 515 | Data Science Overview | 3 |
| DS 520 | Data Mining | 3 |
| ISEC 500 | Cybersecurity Overview | 3 |
| ISEC 545 | Data Privacy and Security | 3 |
| ITMGMT 510 | Managing the Technology Project | 3 |
| ITMGMT 570 | Maintaining the Technology Infrastructure | 3 |
| ITMGMT 575 | Technology Implementation and Change | 3 |
Depth of Study: Computer Science (6 Credits)
| CS 624 | Full-Stack Development I | 3 |
| CS 628 | Full-Stack Development II | 3 |
Capstone (3 Credits)
| CS 687 | Computer Science Capstone | 3 |