Program Overview

Master in Interdisciplinary Data Science

General Info

• Faculty working with students: Varies
• Students: 35-40
• Students receiving Financial Aid: Some merit-based scholarships are available for MS students.
• Part time study available: No
• Application terms: Fall
• Application deadline: January 29

Program Description

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.

Other Requirements: an interview may be required in addition to all Graduate School requirements.

Statistics

• Interdisciplinary Data Science: Master's Admissions and Enrollment Statistics
• Interdisciplinary Data Science: Master’s Career Outcomes Statistics

Application Information

Application Terms Available

• Fall

Application Deadline

• January 29

Graduate School Application Requirements

• Transcripts: Unofficial transcripts required with application submission; official transcripts required upon admission
• Letters of Recommendation: 3 Required
• Statement of Purpose: Required
• Résumé: Required
• GRE Scores: GRE General (Optional)
• English Language Exam: TOEFL, IELTS, or Duolingo English Test required for applicants whose first language is not English
• GPA: Undergraduate GPA calculated on 4.0 scale required
• 1 page Essay on Leadership and Teamwork
• 2 minute video

Department-Specific Application Requirements

The ability to communicate effectively is crucial to being a successful data scientist. All the technical wizardry in the world means nothing if you are unable to convince others of the importance of what you have done. With that in mind, we would like you to submit a 3-5 minute video in which you tell us about a project you have worked on.

The project could be from work experience, a class, or a personal interest. You should act as though you are giving this presentation to someone who is very intelligent and is familiar with data science, but is not necessarily a data scientist themself. You want to be sure to communicate to this person both what you did and why they should care.

The goal of this presentation is not to show off your technical prowess, but rather to demonstrate your ability to think critically about a project and effectively translate what you learned to make it accessible to a broad audience. You may assume the person to whom you are presenting can interpret well-labelled graphs and figures comfortably, and is familiar with statistics, but does not know (or care) much about the more technical aspects of data science.

Your presentation should be no longer than 5 minutes. We will stop listening at the 5-minute mark to be fair to all applicants. You may use slides or visual aids if you wish, but they are not required. In at least some part of the video, we should be able to verify that you are the one presenting by seeing you speaking.

Writing Sample

None required

We strongly encourage you to review additional department-specific application guidance from the program to which you are applying.