Duke University Master in 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're cultivating a new type of quantitative thought leader who uses computational strategies to generate innovation and insights.
Duke's Master in Interdisciplinary Data Science program 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.
The Master in Interdisciplinary Data Science program is structured to connect technical learning and expertise with the many domains in need of data insights. The true power of data in the twenty-first century lies in that connection and our curriculum is developed around the belief that harnessing this power requires both interdisciplinary training and experience with team-based science.
We want to give all our interested students a chance to learn more about the program with a Facebook Live Event Q+A, held on Thursday, January 31, 2019.
Director Tom Nechyba and MIDS student Jason Chang discussed the Master in Interdisciplinary Data Science (MIDS) program, application requirements, data science, life at Duke and answered some of your questions! This is a wonderful opportunity to learn as much as you can about MIDS and strengthen your application!
The Duke University Master in Interdisciplinary Data Science (MIDS) is a two-year program where students will 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.
Experience the full range of the data science ecosystem and graduate as an expert in at least one analytical approach or branch of technology.
The Duke University Master in Interdisciplinary Data Science will help you develop the skills you need to be successful — communication, problem-solving, critical thinking, creativity, and data analysis.