SYS 6018
Data Mining
Course Description
SYS 6021, SYS 4021, or STAT 5120
Data mining describes approaches to turning data into information. Rather than the more typical deductive strategy of building models using known principles, data mining uses inductive approaches to discover the appropriate models. These models describe a relationship between a system's response and a set of factors or predictor variables. Data mining in this context provides a formal basis for machine learning and knowledge discovery. This course investigates the construction of empirical models from data mining for systems with both discrete and continuous valued responses. It covers both estimation and classification, and explores both practical and theoretical aspects of data mining. Prerequisite: SYS 6021, SYS 4021, or STAT 5120.
Instructors
Afsaneh Doryab
Fall 2026
Michael Porter
Fall 2025
Michael Albert
Spring 2022
William Scherer
Spring 2022
Matthew Gerber
Fall 2018
Allan Thompson
Spring 2018
William Basener
Spring 2016
Abigail Thompson
Spring 2015
Donald Brown
Spring 2014
Michael Vedomske
Spring 2014
John Elder
Spring 2010