Keywords: workflow, case studies, data science, teaching, education, RLadies, GitHub, Slack
An increase in demand for training in statistics and data science has led to an increase in computing, but this is not sufficient for teaching these topics. This talk will discuss a successful framework for teaching statistics and data science (described by Nolan and Speed in 1999) using in-depth workflows and case studies derived from interesting problems, with nontrivial solutions that leave room for different analyses. We will also discuss other useful tools for teaching data science, including GitHub Classroom and Slack. Finally, we discuss how these tools have been used to democratize data science to gender and ethnic minority populations that struggle to enter the field.