Frequently Asked Questions


Q: Who should apply?

Anyone interested in advancing their career or changing career paths by developing interdisciplinary skills is encouraged to apply.

Q: How is a Master in Interdisciplinary Data Science (MIDS) degree different from a degree in statistics, math, or computer science?

Our curriculum is broader than traditional graduate programs in individual academic departments and has a stronger emphasis on technical computing skills, practical experiences, and teamwork.

Q: How is a Duke Master in Interdisciplinary Data Science (MIDS) ​​degree different from a degree in business analytics?

Our curriculum emphasizes a deeper understanding of the statistical and mathematical theory behind the tools used in data projects than traditional business analytics programs. We welcome students who want to apply data science to the problems they are most passionate about, including (but of course not at all limited to) problems in business, government, public policy, biomedical science, journalism, and the humanities.

Q: How is a Duke MIDS degree different from a degree in information systems?

Our curriculum emphasizes modeling, analyzing, and interpreting data more than traditional information systems programs. This approach benefits students who want to work outside of business settings in addition to those who want to work in business settings.

Q: Does the Master in Interdisciplinary Data Science (MIDS) program have STEM accreditation?

Yes, Duke MIDS is a STEM-designated degree program, giving international students who meet certain requirements up to 36 months to gain work experience in the U.S. after degree completion.

Q: How long will it take to complete the Masters program?

MIDS is a full-time, two-year program.

Q: Is the degree offered online?

No, we do not currently have an online program.

Q: Is work experience required?

We anticipate many of our students will have work experience, but it isn't required.

Q: Are international students eligible to apply?

Yes, MIDS is a full-time degree program and qualifies for a visa. International applicants are encouraged to apply as early as possible in order to allow ample time to clear the student visa process. Non-citizens residing in the U.S. are encouraged to apply early as well.

Applications can, and should, be submitted in advance of supporting documents, such as recommendation letters, transcripts, and language test scores.


Q: What is the admissions committee looking for?

We want creative, self-motivated students who are passionate about using data to solve problems. We'll look for evidence that you've made efforts to learn about data science and that you're confident data science is the right path for you.  

We'll also look for evidence that you'll succeed in analytical, technical, and professional or interdisciplinary domains. One of the most common pitfalls is failing to address all three of these domains in your application.  

We're particularly excited to welcome students who want to apply data science to topics in which they already have deep expertise. Although certainly not required, we value compelling stories about specific problems you want to solve.

Q: Who should write my letters of recommendation?

Your recommendation writers should tell us about your quantitative skills, your passion for data, your motivation for learning, and your ability to work well with others. They should be the people who know you best and want you to succeed.

If you've graduated from an academic program recently, we recommend including at least 2 letters from professors or advisors. If you've been in the workforce for a while, we recommend including letters from supervisors or mentors.

If you haven't taken quantitative classes in your undergraduate or graduate programs, we recommend that you find letter writers who can give evidence of your analysis and programming skills.

Letters of recommendation from co-workers, people you have supervised, friends, or family members will not be accepted. In all cases, your letter writers should provide specific examples to support why they believe you have the skills or qualities they say you have.

Q: Can I transfer credits from another institution?

Unfortunately, no, you cannot transfer credits from another institution at this time.

Q: Do I have to have a certain kind of degree to apply? Are there any course prerequisites?

Applicants must have received a bachelors degree, but that degree can be in any discipline, and there are no specific prerequisite classes to be able to apply or be admitted.

However, students must demonstrate their ability to succeed in quantitative, analytical, and technical classes.

If you haven't taken these types of classes while in school, you must provide evidence of your aptitude or ability to learn in these areas through online classes, portfolios, code repositories, or other similar mechanisms.

Q: What kind of employment statistics do your students have?

This is the second year of the MIDS program, so we don't have employment statistics yet. However, placing our students in professional or academic positions they're excited about is a primary goal of our curriculum, so we look forward to reporting our progress towards that goal in future years.

Q: Can I enroll in this program while working part time?

Unfortunately, no, MIDS is a full-time, on-campus program that will require your full attention.

The class schedules and time investment required to succeed make it infeasible for students to be working professionally while enrolled.

Q: What educational background is required for admission?

We encourage applications from individuals who come from a range of academic backgrounds.

Q: Are the GRE and/or TOEFL scores required for admission?

GRE scores are required. If English is not an applicant's first language, TOEFL scores are also required.

Q: How do I apply to MIDS?

Applicants can apply directly through the Duke Graduate School:

Applications are closed at this time.

Q&A with Tom and Jason

Tom Nechyba and MIDS student Jason Chang discuss the Master in Interdisciplinary Data Science (MIDS) program, application requirements, data science, and life at Duke!