Why Interdisciplinary Data Science?

The Duke University Master in Interdisciplinary Data Science (MIDS) is home for creative problem-solvers who want to use data strategically to advance society. We are cultivating a new type of quantitative thought leader who uses disruptive computational strategies to generate innovation and new insights.

MIDS combines rigorous computational and technical training with field knowledge and repeated practice in critical thinking, teamwork, communication, and collaborative leadership to generate data scientists who can add value to any field.

All fields need data scientists

You want to use data to advance the industry or field you are most passionate about.

Effective data scientists need depth and breadth

Data scientists who have proficiency in diverse ways of thinking and deep content expertise innovate most effectively.

World problems require data scientists with diverse backgrounds

Data analysis and creative engineering need to be integrated with nuanced domain knowledge, collaborative leadership, and effective management skills to harness data’s full potential.

There has never been a better time to be a data scientist at Duke, and I'm delighted to be able to partner with departments to deliver the interdisciplinary curriculum that's a Duke signature.

I'm thrilled about the network of partnerships around the university that will distinguish this degree as one that allows students to take data science into many different domains.

Program Overview

Photo of Jana Schaich Borg
Jana Schaich Borg
Director of Curriculum, MIDS

Duke MIDS is a two-year program designed to help meet the need for knowledgeable data scientists who can answer important questions with data-backed insights.

All MIDS students complete a set of eight core courses that cover critical topics in statistics, machine learning, database management, data wrangling, data communication, analytical thinking, team management, and ethics. The core courses are designed to fit together as a cohesive set of learning experiences, and ensure that students have repeated practice interpreting and reporting the results of analyses on real data sets.

Accompanying these core courses, students choose a set of approximately eight electives that deepen their expertise in a methodological or domain area.

Students culminate their experience with a capstone project that will be completed over the course of at least one year with mentoring from Duke’s world-class faculty.

Why Duke MIDS?

World-renowned faculty

Work with Duke’s elite faculty in fields across the university, including computer science, statistics, math, economics, political science, sociology, medicine, neuroscience, law, and history.

Personalized pathways

Experience the full range of the data science ecosystem and graduate as an expert in at least one analytical approach or branch of technology—you decide where to pursue breadth vs. depth of knowledge.

Diverse student body

Study and collaborate with talented and passionate students of different ages, backgrounds, and skill sets.

Comprehensive training

Develop quantitative acumen, technical expertise, domain knowledge, leadership skills, and project management experience all in one program.

Collaboration across disciplines

Graduate knowing how to work with any kind of group, and being able to explain the actionable significance of analyses to any kind of audience.

Critical thinking about real problems

Practice applying data science concepts to contemporary problems throughout the two years of the curriculum, so that you graduate being able to think through any computational challenge logically and methodically.

Who Should Apply?

MIDS is open to all applicants who demonstrate a passion for data analysis, a mastery of analytical reasoning, an aptitude for learning quantitative and technical skills, and compelling academic or professional achievement.

We welcome applicants of any age and background, including (but not limited to) recent college graduates with quantitative majors, database engineers who have been in the IT field for years, government professionals who want to integrate data science into federal or local offices, and journalists who want to incorporate data mining into their investigative skills.

Due to our comprehensive approach, our application process requires applicants with primarily quantitative backgrounds to demonstrate their commitment to excelling in the problem-solving, communication, and team-building aspects of data science. Likewise, applicants without quantitative backgrounds are asked to demonstrate their commitment to learning quantitative concepts and skills quickly through mechanisms like online classes or recommendations from colleagues with strong quantitative track records.

We provide resources for students to review and learn critical concepts and skills before beginning the core courses, so that all students can begin the core courses on a level playing ground.

Contact MIDS

More details about the program and application process will be posted soon.

Stay tuned and sign up for our mailing list to be notified of updates!