Data Science Masters
The Masters of Science in Data Science degree is a professional master’s program designed for students who want to begin or advance their careers in data science. The program is available full-time or part-time. Classes begin every fall quarter and meet in the evenings on the University of Washington campus.
The industry-relevant curriculum gives you the skills to extract valuable insights from big data. In this program, you will learn expertise in statistical modeling, data management, machine learning, data visualization, software engineering, research design, data ethics, and user experience to meet the growing needs of industry, not-for-profits, government agencies, and other organizations.
Graduate Data Science Options
The goal of this option is to educate students in the foundations of data science. The “Data Science Option” aims to educate the next generation of thought leaders who will apply new methods for data science.
The following departments already have a Graduate Data Science Option, offered either through a Masters or PhD program:
- Astronomy
- Atmospheric Sciences
- Bioengineering
- Biology
- Biomedical Informatics and Medical Education
- Chemical Engineering
- Chemistry
- Civil & Environmental Engineering
- Earth and Space Sciences
- Evans School of Public Policy & Governance
- Genome Science
- Health Economics & Outcomes, UW School of Pharmacy
- Mechanical Engineering: both Masters of Science and PhD options
- Molecular & Cellular Biology
- Molecular Engineering and Sciences
- Psychology
- School of Aquatic and Fishery Sciences
PhD students in Applied Mathematics, Mathematics, Computer Science & Engineering, Oceanography, or Statistics should only enroll in the Advanced Graduate Data Science Option (see below).
Advanced Graduate Data Science
The advanced data science option targets students who seek to develop new data science methods and build new data science tools. It focuses on creating an interdisciplinary cohort of data science students taking the same set of advanced data science courses.
- Applied Mathematics: Contact Lauren Lederer and Matthew Lorig
- Astronomy: Contact Andrew Connolly
- Atmospheric Sciences
- Biology: Contact Krista Clouser and Tom Daniel
- Biomedical Informatics and Medical Education
- Chemical Engineering: Contact Allison Sherrill and David Beck
- Computer Science & Engineering: Contact Elsa Binag and Magda Balazinska
- Evans School of Public Policy & Governance
- Genome Sciences: Contact Brian Giebel and William Noble
- Mathematics: Contact John Palmieri
- Mechanical Engineering
- Oceanography: Contact Michelle Townsend and Mark Warner
- Psychology: Contact Ariel Rokem
- Statistics: Contact Ellen Reynolds