Her data science course emphasizes “reproducible computation”, a documented process of how data is treated in order to replicate the results in the future. She edits the Citizen Statistician blog and offers the annual Duke DataFest, a hackathon for working with data. She quite literally wrote the book on the subject, and her open, online course Master Statistics with R certifies thousands of students a year.
Mine Çetinkaya-Rundel, Director of Undergraduate Studies and an Associate Professor at Duke University, tackles these problems head-on. That outcome requires a consistent level of training, across diverse datasets. It’s a challenge to keep the material engaging for everyone.Īt the same time, teachers want the next generation of data scientists to be able to analyze any dataset they come across in the future with the same level of rigor used in the classroom. Data science is a melting pot of disciplines: students from Anthropology to Political Science to Education all sign up for the same course.
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