MATH179 HM - Mathematics of Big Data

Credit(s): 3

Instructor(s): Gu

Offered: Fall

Description: This is a course in how to utilize data: infer, predict, coerce, and classify. The course covers a large breadth of material, spanning supervised and unsupervised learning, recommender systems, and Bayesian modeling, to a high level of mathematical rigor. Students will learn how to use mathematical techniques to process big raw data including data indexing, visualization, structuring, representing, and reducing data dimension. Upon successful completion of the course, students should be equipped to enter industry as a data scientist, read active research in the field of machine learning, and approach huge (data and otherwise) problems seen in the real world. Students will become comfortable using GitHub basic tools for use in developing and deploying models.

Prerequisite(s): CSCI005 HM and (MATH019 HM or MATH032 CM/PO/PZ/SC) and (MATH073 HM or MATH060 CM/PO/PZ/SC)