11 Items

  1. Stories

    Data Science Across Disciplines Class of 2024

    This J-term, midd.data mounted our fourth iteration of Data Science Across Disciplines, and it was another big success! Six instructors—Alex Lyford (Mathematics and Statistics), Bert Johnson (Political Science), Pete Nelson (Geography), Katherine O’Brien (Center for Community Engagement), Conor Stinson (‘06.5) and Michael Czekanski (‘20)—worked with fifty students spanning fourteen different declared majors to solve a range of challenging, data-driven problems, while learning the necessary data science and computational tools along the way!

  2. EventsStories

    Joshua Kalla Lecture

    On October 9, Yale political scientist Joshua Kalla visited Middlebury to give a talk on “Polarization and persuasion in American Politics,” co-sponsored by midd.data, the Conflict Transformation Collaborative, and the Rohatyn Center for Global Affairs. Professor Kalla discussed evidence from field experiments demonstrating that under certain conditions, perspective taking and storytelling may shift exclusionary attitudes and policy preferences.

  3. StoriesVideos

    Another great summer Intro to Data course!

    This summer midd.data offered our credit-bearing “Introduction to Data” summer course for a second time, following our successful launch last year. This course is designed to provide students from backgrounds that have historically been underrepresented in data science with new opportunities to learn about and participate in the field. 

    Video
  4. Stories

    Introduction to Data 2022 Summer Course

    In the summer of 2022, midd.data launched a new credit-bearing “Introduction to Data” summer course designed to provide students from backgrounds that have historically been underrepresented in data science with new opportunities to learn about and participate in the field. 

  5. Stories

    Data Science Across The Disciplines: A New Course

    | by Caitlin Myers

    This winter term five faculty colleagues from Math, Art History, Biology, Economics, and Japanese designed and piloted a new course blending a traditional introduction to data science with immersive project-based applications across four disciplines. Students with no prior data science experience spent their mornings learning how to use the statistical software package R to wrangle and extract meaning from data, and their afternoons critically applying these skills to research projects on topics ranging from seventeenth-century Dutch art to tick-borne disease to Japanese pop culture to abortion policy.

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