46-895 Special Topics in Business Analytics

6 units, Carnegie Mellon University

The recent explosion in largescale highresolution data enables managers to ask and answer questions regarding businesses and consumers at a whole new level. Managers are faced with data about businesses and consumers that are growing faster than they can be utilized. This course provides MSBA students with basic concepts and techniques of data mining as well as when and how they can be applied in various business applications. Realworld examples are drawn from marketing, finance, and other areas for illustration. Throughout the course, we will use R, a powerful opensource statistical language and one of the mainstream tools in data mining and business analytics. With this tool, you will learn about various exploratory and predictive data analytics techniques such as Nave Bayes classifier, nearest neighbor approaches, decision trees, clustering algorithms, etc.

Prerequisites: none listed

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