Statistical Learning and Big Data

This course will introduce modern statistical learning tools with a focus on tools developed for big data. It covers three interconnected components: statistical machine learning methods, the underlying algorithms, and computational tools. This course will focus on the principal techniques to analyze data from start to finish: managing large data, exploring patterns, framing statistical problems, building efficient computational algorithms, and writing reports. Topics will include data management, feature engineering, clustering, convex optimization algorithms, tree/ensemble methods, and predictive modeling. Non-biostatistics students who have taken 2510 and 2511 may request permission to enroll.