This two-day workshop provided a gentle introduction to supervised machine learning: concepts, methods, and R code. Participants learned how to train and assess predictive models with several common machine learning algorithms, as well as how to do feature engineering to improve the predictive accuracy of their models. We focused on teaching intuitive explanations of the models and best practices for predictive modeling. Along the way, we introduced several core tidymodels packages, which provide a grammar for modeling that makes it easy to the …