Our mission is to prepare data scientists to solve real-world problems through critical thinking, collaboration, communication, and the ethical and judicious application of cutting-edge data science methods. Our interdisciplinary focus readies students to apply innovations across disciplinary boundaries and be impactful across a wide range of careers. Our project-based learning model and training in cloud, databases, and distributed systems ensure our students are ready to deploy solutions immediately upon graduation.
We do so through a curriculum that teaches, provides regular opportunities to practice, and gives regular feedback on:
- Critical thinking in the interpretation of data, clarifying the problem one seeks to solve, understanding how one’s statistical analysis relates to the substantive problem of interest, and how data can guide evidence-based decision-making.
- Solving data science problems effectively in teams by fostering psychological safety, helping colleagues be more effective, communicating clearly, and by establishing mutual expectations.
- Creating and deploying tools on a range of industry-relevant technology platforms, including cloud and distributed compute and data storage systems.
- Recognizing the ethical implications of the choices one makes as a data scientist and being intentional about how one engages with those issues.
- Communicating conclusions, recommendations, and uncertainty to audiences from diverse technical, substantive, and social backgrounds.
Duke MIDS Program Overview
Our program is developed around the belief that harnessing the power of data requires both interdisciplinary training and experience with team-based science.
- We’ve 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.
- Our 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.
- Our 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. We also offer opportunities to pursue advanced technical topics related to the core courses.
- We 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.
- In order to train data scientists that are both technical experts and can apply their expertise to different topics, our training is a commitment of four semesters.
MIDS invites broad collaboration to connect data science with real-world problems. These problems are as varied as using social media to track health outcomes to visualizing thematic trends in literature across centuries. Duke’s interdisciplinary and collaborative research culture makes our campus an ideal place for such a program.