Master of Science in Data Science

The Master of Science in Data Science (MSDS) is an inherently interdisciplinary field that requires effective integration of a domain to provide data and a context for its exploration, statistics, and computer science.
Data science professionals are in high demand in nearly every field, from global businesses like Amazon to sectors like health care and government security. According to Glassdoor, data scientists and data engineers are two of the best jobs in the U.S., based on salary, job openings, and job satisfaction. With the hands-on experience and internship options our MSDS program provides, you are prepared for a myriad of opportunities to work in and advance your data science career.
Courses focus on data acquisition, data management, data mining, data governance, data analytics, artificial intelligence, machine learning, deep learning, programming for computing, big data systems, and mathematics and statistics needed to deliver data science projects. You will also maintain the professional skills required to advance in the data science field.
This program will provide you with the experience and leadership identity required to influence the way that data science is implemented and consumed in any corporation or government organization.
The Master of Science in Data Science program is designed around the Body of Knowledge set forth by the Association for Computing Machinery (ACM), which ensures students will be able to understand their data and know what they can expect to learn from the data. They will also be able to select the right tools and techniques to get the job done.
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 nonprofit organization.
The capstone is the platform that exhibits the synthesis of the 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 includes a public presentation designed to demonstrate mastery.
Learning Outcomes
The Master of Science in Data Science will prepare students to:
Integrate a foundational knowledge of all areas of advanced data science (General Data Science Knowledge)
Apply fundamental principles and practices of advanced data science (Data Science Principles and Practices)
Apply critical and ethical thinking to solve problems in advanced data science (Critical and Ethical Thinking)
Evaluate data to inform decisions and solve problems in advanced data 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).

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.