| Sumario: | This course introduces Enterprise Miner while demonstrating two common applications: segmentation and predictive modeling. It starts with a brief overview of the software and then covers segmentation and predictive modeling using a case-study approach based on real-world data. Upon completing the course, learners will have a basic, working knowledge of how to use Enterprise Miner to perform data mining and machine learning tasks. Participants should have a quantitative background and (ideally) some basic understanding of predictive models, including regression. Learn how to use Enterprise Miner to perform data mining and machine learning tasks Explore the fundamentals of predictive modeling and clustering Discover how to build, compare, and deploy predictive models using SAS Enterprise Miner Learn how to perform, interpret, and profile a cluster analysis using SAS Enterprise Miner Jeffrey Thompson is a Senior Analytical Training Consultant with the SAS Institute and has worked with SAS since the early 90s. A former associate professor of statistics at North Carolina State University, Jeffrey has been published in the International Statistical Review, the Austrian Journal of Statistics, and other peer-reviewed journals. He holds a bachelor's degree in mathematics, a master's degree in statistical computing, and a PhD in statistics.
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