MG 5500 - Data Driven Decision Making

This course introduces students to key methods used to extract information from large datasets and apply that data to business problems. Students will learn how to identify quality data using key concepts like classification, data reduction, and model comparison, and interpret that data using tools like decision trees and logistic regressions. In addition, data preparation and visualization techniques are addressed to provide students with skills in visual representation methods. (4 credits)