You don’t settle for the first answer you receive. Or the simplest one.

You can dig deeper than most people, and you enjoy puzzles and pondering the big questions. You relish the challenge of diving into a massive amount of information and surfacing with usable and actionable insights. You have the stamina and clarity of mind to apply knowledge to the real world. And you want to make a difference.

If this sounds like you, we want you at the Data Science Institute at the University of Virginia.

We are creating leaders in the cutting-edge field of data science and equipping our graduates with the technical and practical skills to transform the modern world.

Graduates from our Master of Science in Data Science (MSDS) program are changing business, medicine, engineering, technology and public policy, just to name a few fields. You will leave us, after an intense 11 months, as a data scientist poised to tackle the world’s biggest problems.

What does the MSDS program offer?

To meet the growing demand for skillful, agile data scientists, the Master of Science in Data Science (MSDS) degree at the University of Virginia is a rigorous 11-month professional master’s program.

Beginning in July and ending the next year in mid-May, this fast-paced program includes courses taught by faculty from the Departments of Computer Science, Statistics, and Systems and Information Engineering.

The MSDS program offers distinctive advantages:

An integrated curriculum that focuses on hands-on learning
A concluding capstone project that gives students real-world experience
An interdisciplinary focus that spans across the University into numerous fields of study
A vibrant cohort experience
A powerful preparation for and connection to industry-leading careers
Funding for professional development
A historic university blazing the trail to the future through advanced research and education

What does the curriculum look like?

The MSDS program necessarily exists outside the traditional curricular structure, but in its unorthodoxy, the program is a forward-looking blueprint for a world in which data science plays an increasingly larger role.

The curriculum is tightly prescribed, with about 80% of the material common to all students. Several large, complicated data sets are woven across courses to increase the program’s cohesion. And students will consistently work together in teams, building strong relationships and practical skills in the process.

The Master of Science in Data Science program uses the spiral learning framework: Students begin by acquiring a foundation in languages, computation and linear modeling and then build on those skills to begin the practice and application of data science.

At the conclusion of the program, students will address an important data science challenge with their capstone projects. Before presenting their projects, students will create a proposal outlining their objectives and will be mentored and evaluated by faculty members from different disciplines.

Duncan Rule

Gabriel Rushin

Brian Sachtjen

Kaustav Saha

Katherine Schinkel

Timothy Schroeder

Prasad Seemakurthi

Pragati Shah

Nicole Shintaku

Tianye Song