IE 529 - Stats of Big Data & Clustering

Semesters Offered

Stats of Big Data & ClusteringIE529A68102ONL4 -    Carolyn L Beck

Official Description

This course will cover various foundational topics in data science. Parametric and non-parametric methods. Hypothesis testing; Regression; Classification; Dimension reduction; and Regularization. Unsupervised and semi-supervised learning, along with a few case studies. Course Information: 4 graduate hours. No professional credit. Prerequisite: MATH 415 and IE 300 or equivalent. All ISE graduate students and students enrolled in the Master of Science in Advanced Analytics (MSAA) are eligible to take the course.