Why 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 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.
Dear Prospective Student,
Thank you for your interest in Duke MIDS!
This MS degree is based on a vision of data science as an inherently interdisciplinary and team-based endeavor. It borrows technical tools from a variety of quantitative disciplines and connects them to data-driven inquiry in virtually all disciplinary domains.
The data scientists we'll graduate will have technical depth in one or more quantitative methodologies that is complemented by broad awareness of existing and emerging analytical tools and an ability to leverage technical and analytical proficiency to solve hard problems as part of a team.
Our graduates will be able to communicate effectively with those whose expertise lies in a domain area of the problem to be solved rather than in quantitative data techniques, and will be able to use critical thinking skills to cross disciplinary domains. The curriculum we offer includes interdisciplinary training within the quantitative sciences, exposure to data-driven problems in a variety of disciplines, and direct experience in interdisciplinary team-based science.
Nick Eubank and Michael Akande
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