IE 529

spring 2018

All Classes

Stats of Big Data & Clustering

Credit: 4 hours.

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.

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.

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Detail	Status		CRN	Type	Section	Time	Day	Location	Instructor