This course provides an introduction to data mining by exposing the theory behind the analytical concepts. It discusses data mining techniques and their use in strategic business decision making. This is a hands-on course that provides an understanding of the key methods of data visualization, exploration, association, classification, prediction, time series forecasting, clustering, induction techniques, neural networks, and others. During the semester-long course, students work in teams on solving a business problem of their choice, using data mining tools and applying them to data (e.g., SPSS modeler). Data Mining provides a solution to organizations requests for emerging operational patterns that may add value to their business. The course includes the development of concepts used for building frameworks needed in analyzing useful patterns in databases through the application of practical methods.
Prerequisite(s): MBAMS 640 AND College of Management graduate. Department permission required.