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IEMS 402-0

Statistical Learning

1 Unit · Graduate

The amount of data in our world has been exploding and analyzing large data sets is a central societal challenge. The course introduces statistical principles and computational tools for analyzing big data. Topics include statistical modeling and inference, model selection and regularization, scalable computational algorithms, and more.

Prerequisites & course information

Prerequisites: Graduate standing students that have completed IEMS 401-0 or equivalent (i.e. graduate-level statistics and probability).

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