Data Mining for Business Analytics

Data Mining is the process by which useful information is extracted from large amounts of data. This course is designed to provide students with the necessary tools and techniques to perform data mining and business analytics. This course is intended as an introductory module targeted at individuals who plan to work with data (modeling, data management) as well as towards those who will work with data scientists. While the course will primarily focus on modeling and evaluation, it will also include data preparation and examination. Modeling techniques covered include dimension reduction, regression methods, decision trees, clustering, and other ad-hoc methods. Emphasis will be placed on the entire context surrounding data mining, which includes the business problem, data processing, modeling, evaluation and deployment. Students will be expected to implement these techniques in big-data case studies throughout the semester. CIS 3920 is cross-listed with STA 3920. Credit will not be given for both CIS 3920 and STA 3920. These two courses may substitute for each other in the F-replacement policy.

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