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The Master in Interdisciplinary Data Science (MIDS) at Duke University is a STEM-designated, highly flexible, and application-focused program designed to train the next generation of data scientists who can collaborate across disciplines and apply data-driven insights to real-world challenges.
Unlike traditional data science programs, Duke MIDS emphasizes interdisciplinary thinking, ethical data practices, and project-based learning. It integrates coursework in statistics, computer science, machine learning, data communication, and domain-specific applications, preparing graduates for impactful careers in industry, nonprofits, government, or academia.
Program Format & Duration
Full-time, on-campus program based in Durham, NC
Duration: 2 years (4 semesters)
Optional summer internship or research placement
STEM-designated (OPT extension eligible)
Fall intake only
Core Curriculum Components
Duke MIDS provides a strong technical foundation while allowing students to explore specific domains of interest.
Core Courses
Technical Foundations
Computational Data Analysis (Python, R)
Machine Learning and Statistical Modeling
Data Management Systems
Algorithms and Optimization for Data Science
Data Ethics and Communication
Data Communication and Visualization
Data Ethics, Law, and Policy
Teamwork and Leadership for Data Science
Interdisciplinary Applications
Courses and projects across domains like health, environment, public policy, social science, and economics
Opportunity to tailor coursework through electives offered across Duke's schools (e.g., Fuqua School of Business, Sanford School of Public Policy, School of Medicine)
Electives & Tracks (Sample Areas)
Health Analytics
Education & Social Impact
Computational Journalism
Climate & Environment
Finance and Economics
Text Mining/NLP
Experiential learning is a cornerstone of the Duke MIDS program, ensuring students apply classroom learning to real-world problems.
Data+ Summer Research Program
A paid, 10-week summer experience working with faculty and external partners on data-centered projects
Open to students between first and second years
Encourages teamwork, communication, and public dissemination of findings
Capstone Project
Year-long, team-based engagement with external partners (industry, government, nonprofits)
Students scope, design, and implement an end-to-end data science solution
Past sponsors include: RTI International, World Bank, Duke Hospital, City of Durham, and Red Hat
Internships
While not required, many students complete internships during the summer
Duke provides strong support through career services, alumni network, and faculty connections
Experiential Learning
Experiential learning is a cornerstone of the Duke MIDS program, ensuring students apply classroom learning to real-world problems.
Data+ Summer Research Program
A paid, 10-week summer experience working with faculty and external partners on data-centered projects
Open to students between first and second years
Encourages teamwork, communication, and public dissemination of findings
Capstone Project
Year-long, team-based engagement with external partners (industry, government, nonprofits)
Students scope, design, and implement an end-to-end data science solution
Past sponsors include: RTI International, World Bank, Duke Hospital, City of Durham, and Red Hat
Internships
While not required, many students complete internships during the summer
Duke provides strong support through career services, alumni network, and faculty connections
Progression and Future Opportunities
Graduates from the Duke MIDS program are exceptionally well-prepared for multidisciplinary data roles that demand both technical fluency and domain insight.
Career Outcomes
Typical roles include:
Data Scientist / Machine Learning Engineer
Policy Analyst (Data Focus)
Health Informatics Specialist
AI Product Manager
Research Data Analyst
Business Intelligence Developer
Social Impact Data Strategist
Top Employers
Graduates have been hired by:
Google, Amazon, IBM, Microsoft
Booz Allen Hamilton, Deloitte, RTI
National Institutes of Health (NIH), EPA
Nonprofits and think tanks (e.g., World Bank, Urban Institute)
Startups and social enterprises in health, edtech, climate, and finance
Further Study
Some MIDS graduates pursue:
PhDs in Data Science, Public Policy, or Computational Social Science
Dual degrees (MBA, MPP)
Research roles in academia, government labs, or NGOs
Bachelor’s Degree & GPA: Hold a bachelor’s degree (U.S. 4-year or international equivalent) with a minimum undergraduate GPA of 3.0.Transcripts: Upload unofficial transcripts with your application and submit official ones upon admission.Letters of Recommendation: Provide three letters of recommendation. Statement of Purpose: Submit a statement of purpose.Résumé/CV: Submit a current résumé/CV outlining academic, professional, and technical experience.GRE Scores: GRE General Test scores are optional.English Proficiency (International): Submit TOEFL, IELTS, or Duolingo scores if English isn’t your first language (waiver possible)Teamwork Essay: Include a one-page, single-spaced essay describing your approach and experience working in teams.Video Response: Provide a recorded video response to an application prompt.Application Deadline & Interview: Apply by February 13, 2025 for fall entry—an interview may be required in March, with decisions by March 31. Three‑Year Bachelor’s Degrees: Duke MIDS accepts three-year undergraduate degrees, but candidates are advised to contact grad‑[email protected] for confirmation of equivalency WES Evaluation: While official transcripts (with certified English translations if needed) are required, a WES or similar credential evaluation is recommended but optional to confirm U.S.-equivalent degree credentials .Data AnalystData ScientistBusiness AnalystStatisticianStatistical ProgrammerSAS ProgrammerMachine Learning EngineerDeep Learning EngineerAI ResearcherData EngineerBI DeveloperData ArchitectAnalytics ConsultantAdvisory ConsultantQuantitative AnalystRisk AnalystOperations AnalystMarketing AnalystResearch ScientistInsights AnalystForecasting AnalystHealthcare Data AnalystFinancial Data AnalystProduct Analyst
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