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PSTAT235

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PSTAT 235 - Big Data Analytics

Statistics & Applied Probability College of Letters and Science

Full Course Title

Big Data Analytics

Instructor Name(s)

STAFF

Course Description

Basics in distributed data storage, retrieval, processing and cloud computing. Overview of methods for analyzing big data from both high dimensional statistics and machine learning - topics chosen from penalized regression, classification/clustering, dimension reduction, random projections, kernel methods, network clustering, graph analytics, supervised and unsupervised learning among others.

Unit Value

4

Maximum number of times course can be repeated for additional credit

0

Maximum Units

4

Prerequisites

PSTAT 131 or PSTAT 231 or Computer Science 165B; and Computer Science 9 or Computer Science 16. A minimum letter grade of C or better must be earned in each course.