Introduction to Data Science (DATA*6100)

The course includes an introduction to the methods of modern statistics such as splines, general additive models, principal components analysis, and classifiers. Students learn resampling methods such as bootstrap, cross-validation, boosting, and bagging. Methods of model selection include search-and-score and regularization, and students practice communicating technical ideas to a non-technical audience, including via data visualization.