Master of Science in Data Science

2 Years On Campus Bachelors Program

University of Washington

Program Overview

The Master of Science in Data Science at the University of Washington is a professional graduate programme designed for students who want to build or advance careers in data science. Developed through collaboration among six academic departments, it combines statistics, computer science, machine learning, data management, and human-centred design. Students learn to turn complex datasets into useful insights while developing the technical and communication skills needed to work across different industries. The programme is available in full-time and part-time formats.

Curriculum Structure

The programme requires 45 credits, consisting of eight core courses and a two-quarter capstone project. Students develop practical skills through individual coursework, team-based assignments, and applied data analysis projects.

Core Courses

Students study the foundations of data science through the following courses:

DATA 511: Data Visualization for Data Scientists
DATA 512: Human-Centered Data Science
DATA 514: Data Management for Data Science
DATA 515: Software Design for Data Science
DATA 516: Scalable Data Systems and Algorithms
DATA 556: Introduction to Statistics and Probability
DATA 557: Applied Statistics and Experimental Design
DATA 558: Statistical Machine Learning for Data Scientists

The curriculum also includes DATA 598: Topics in Data Science, which allows students to explore additional subjects in the field. Depending on the course, students work with programming languages such as Python, R, and Java.

Capstone Project – 5 Credits

Students complete a two-quarter capstone project in collaboration with an external organisation. The project is divided into two courses:

DATA 590: Capstone Project Planning
DATA 591: Capstone Project Implementation

Students work on a real-world data science challenge, applying their knowledge of data management, statistical modelling, machine learning, and software development. The experience also develops teamwork, project planning, and communication skills.

Study Options and Duration

Full-Time: Approximately 1.5 years, with two courses per quarter. Students attend classes two evenings per week.
Part-Time: Approximately 2.5 years, with one course per quarter. This format is suitable for working professionals who want to continue their careers while studying.

Both formats follow the same curriculum and provide access to the same faculty and learning opportunities.

Focus Areas

Statistical Modelling and Data Analysis
Machine Learning and Predictive Analytics
Data Management and Database Systems
Data Visualisation and Communication
Software Engineering for Data Science
Scalable Data Systems and Algorithms
Human-Centred Data Science
Experimental Design and Research Methods
Data Ethics and Responsible Data Practices
Applied Data Science and Industry Projects

Learning Outcomes

Students learn how to collect, organise, manage, and analyse large datasets using statistical and computational methods. They develop skills in machine learning, data visualisation, software engineering, and scalable data systems, allowing them to solve practical problems across different industries.

The programme also emphasises ethical data practices, research design, and human-centred approaches to technology. Through collaborative assignments and the capstone project, students gain experience working with real-world data, presenting analytical findings, and developing solutions that meet organisational needs.

Professional Alignment (Accreditation)

The programme is classified under STEM-designated CIP code 11.0401 (Information Science/Studies). This may allow eligible international graduates in the United States to apply for an extended Optional Practical Training period of up to 36 months, subject to applicable immigration requirements. The university does not specify a separate professional or industry accreditation for this degree.

Reputation (Employability Rankings)

The University of Washington's MS Data Science programme has strong connections with the technology and data science industries through its Industry Advisory Board, which includes professionals from organisations such as Amazon, Boeing, Google, Instacart, Meta, Microsoft, Shopify, and Seattle Children's Hospital.

Graduates have pursued careers with organisations including JPMorgan Chase, IBM, Costco IT, Toyota, Northrop Grumman, Zillow, and the Institute for Health Metrics and Evaluation. The programme also provides dedicated career services and an annual Data Science Career Fair to help students connect with employers.

Experiential Learning (Research, Projects, Internships etc.)

At the University of Washington, the MS in Data Science program is designed to provide students with hands-on experience that translates theoretical knowledge into practical skills. Students engage in real-world projects, collaborate with peers, and utilize cutting-edge tools and technologies that are essential in the data science field. The program emphasizes experiential learning through various opportunities, ensuring that graduates are well-prepared for the demands of the industry.

Here are some key aspects of experiential learning in the MS Data Science program:

- Capstone Projects: Students work on team-based capstone projects that tackle real-world data challenges, allowing them to apply their skills in a collaborative environment.
- Internship Opportunities: The program encourages internships with local tech companies and organizations, providing valuable industry experience and networking opportunities.
- Access to Advanced Software: Students gain proficiency in industry-standard tools such as Python, R, SQL, and Tableau, which are integral to data analysis and visualization.
- Research Labs: The university boasts state-of-the-art research facilities, including the eScience Institute, where students can engage in innovative data science research.
- Workshops and Seminars: Regular workshops and guest lectures from industry experts help students stay updated on the latest trends and technologies in data science.
- Collaboration with Faculty: Students have the opportunity to work closely with faculty members on research projects, gaining insights and mentorship from experienced professionals.
- Data Science Community: The program fosters a vibrant community through student organizations and events, encouraging collaboration and knowledge sharing among peers.

These experiential learning opportunities not only enhance your academic experience but also equip you with the skills and connections needed to thrive in the data science field.

Progression & Future Opportunities

The MS in Data Science at the University of Washington equips graduates with the skills and knowledge to excel in a rapidly growing field. Alumni often find themselves in high-demand roles such as Data Scientist, Machine Learning Engineer, and Business Intelligence Analyst. With a strong foundation in data analysis and machine learning, graduates are well-prepared to tackle complex challenges in various industries:

- University Services for Employment: The Career Center offers personalized career coaching, resume workshops, and networking events specifically tailored for data science students. Additionally, the Data Science program provides access to industry mentors and internship opportunities through partnerships with leading tech companies.

- Employment Stats and Salary Figures: According to recent data, over 90% of graduates secure employment within six months of graduation, with starting salaries averaging around $100,000 per year, reflecting the high demand for skilled data professionals.

- University–Industry Partnerships: The University of Washington has established strong collaborations with companies like Amazon, Microsoft, and Boeing, providing students with real-world projects and internship opportunities that enhance their learning experience.

- Long-term Accreditation Value: The program is accredited by the Northwest Commission on Colleges and Universities (NWCCU), ensuring that the education you receive meets high standards and is recognized nationally.

- Graduation Outcomes: Graduates of the program have gone on to work at prestigious organizations, contributing to innovative projects and advancing their careers in data science and analytics.

Further Academic Progression: After completing the MS in Data Science, students have the option to pursue a Ph.D. in Data Science or related fields, allowing them to delve deeper into research and academia. Alternatively, they can explore specialized certifications in areas like Artificial Intelligence or Big Data, further enhancing their expertise and career prospects. This pathway not only broadens your knowledge but also positions you as a leader in the evolving landscape of data science.