Reinforcement Learning is a type of machine learning where a robot learns to make decisions through trial-and-error. In Autonomous Racing, the robot learns through trial-and-error as it drives on the track. In this unit, participants collect data from the track, train and visualize the base model, and then provide feedback to the robot as it learns to race.