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The Basics

Master in Interdisciplinary Data Science (MIDS)

Duke University

Data Science is Interdisciplinary


Social Science Research Institute
140 Science Dr.
Durham , North Carolina, 27705, United States

What We Offer

Summary

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're cultivating a new type of quantitative thought leader who uses 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.


Academic Fields

Statistics, General.
Computer Science.
Computer Programming, Other.
Applied Mathematics, General.

Degrees

Master's Degree, MS, Master of Science


Formats

Full Time

Keywords

data science duke university

Contacts

Courtney Orning

Courtney Orning
Director of Communications
courtney.orning@duke.edu
courtney.orning@duke.edu

Who We're Looking For

Summary

MIDS is open to all individuals 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.


Academic Backgrounds

Computer Science.
Social Sciences, General.
Mathematics and Statistics.
Economics, General.

Target GPA

A- = 3.3-3.6

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