Data science is emerging as one of the most important business disciplines to know and understand. Businesses, governments, and society leave behind massive trails of data as a by-product of their activity. Increasingly, decision-makers rely on intelligent systems and data mining techniques to analyze these data systematically and assist them in their decision-making. In many cases automating the decisionmaking process is necessary because of the speed with which new data are generated. This course connects real-world data from proprietary sources to publicly available social network data from sites like Twitter and Facebook to decision-making. Real-world examples from Finance, Marketing, and Operations are used to illustrate applications of a number of data mining methods. The use of real-world examples and cases places these techniques in context and teaches students how to avoid the common pitfalls of data mining, emphasizing that proper application of data mining techniques is as much an art as it a science. In addition to cases, the course features hands-on exercises with data mining software that will enable students to both build models and evaluate their output. The course is suitable for those interested in working with and getting the most out of data as well as those interested in understanding data mining from a strategic business perspective. It will change the way you think about data in organizations.
This course is taught by Professor Shawndra Hill at the Wharton School of the University of Pennsylvania