Big Data

1 Course Unit

Selected topics from public health and biomedical research where "Big data" are being collected and methods are being developed and applied, together with some core statistical methods in high dimensional data analysis. Topics include dimension reduction, detection of novel association in large datasets, regularization and high dimensional regression, ensemble learning and prediction, kernel methods, deep learning and network analysis. R programs will be used throughout the course, other standalone programs will also be used. Prerequisite: If course requirement not met, permission of instructor required. Prerequisite: BSTA 6210 AND BSTA 6220 1 Course Unit