In this talk we will discuss two statistical computing courses taught as part of the undergraduate and masters curriculum in the Department of Statistical Science at Duke University. The primary goal of these courses is to teach advanced R along with modern software development practices. In this talk we will focus in particular on our adoption of continuous integration tools (github and wercker) as a way to automate and improve the feedback cycle for students as they work on their assignments. Overall, we have found that these tools, when used appropriately, help reduce learner frustration, improves code quality, reduces instructor workload, and introduces powerful tools that are relevant long after the completion of the course. We will discuss several of the classes' open-ended assignments and explore instances where continuous integration made sense and well as cases where it did not.