PSTAT 135 - Big Data Analytics

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.

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

PSTAT 135

0 / 150 Enrolled

Big Data Analytics

Sang-Yun Oh 2.3

M W

14:00 PM - 15:15 PM

82.5% A