• Master in Interdisciplinary Data Science is a two-year program at Duke University.
  • It is an on-campus program offered on a full-time basis.
  • The curriculum they 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.

    • PROGRAM LEARNING OUTCOMES:

    The program is developed around the belief that harnessing the power of data requires both interdisciplinary training and experience with team-based science.

    1. They have created a core group of courses for all MIDS students that’s inspired by the data-to-decision cycle. These courses are centered on marshalling, analyzing, and visualizing data. They create a shared language for students and a common frame of reference for data-driven projects.
    2. The core courses draw on expertise and involve faculty from different disciplines across Duke. By doing so, they reflect the multiple quantitative disciplines that contribute skill sets to data science.
    3. The key aim is to train data scientists who can address a diversity of topics, so students are encouraged to choose electives from different departments across Duke. They also offer opportunities to pursue advanced technical topics related to the core courses.
    4. They teach students the necessary skills to succeed on teams with experts in different fields, fellow data scientists, and stakeholders. This includes leading teams, thinking critically across disciplines, and communicating complex ideas to others.
    5. In order to train data scientists that are both technical experts and can apply their expertise to different topics, the training is a commitment of four semesters.

    CAPSTONE PROJECTS:

    • Capstone projects are one of the most important components of the MIDS program.
    • These year-long projects integrate students into world-class interdisciplinary research projects that can solve real-life problems and be significantly advanced through data science.
    • To ensure MIDS students complete their projects successfully, they will attend workshops and complete assignments throughout the second year that provide guidance, practice, and feedback about students’ teamwork, project management, communication plan, and overall progress in relation to the project.
    • The final deliverables will be evaluated by MIDS core faculty and relevant outside stakeholders on multiple dimensions including students’ ability to communicate effectively to a diverse audience, computational strategy, and creativity.