In POLISCI 150A: “Data Science for Politics,” political science associate professor Adam Bonica uses a project-based curriculum to allow students to explore data-driven predictions in modern politics. With the programming language R, the class’ approximately 50 students tackle problem sets in teams. For example, the most recent problem set challenged each team to find new predictive variables to add to a shared dataset used to make predictions about the midterm elections.