IT 170 - Introduction to Data Mining for Business IntelligenceSemester Hours: 3
Periodically
Data mining is a process of extracting useful information from large databases in business and non-profit entities. Data mining principles encompass: problem definition, exploratory data analysis, dimension reduction, consideration of alternative models, and calibration of models, evaluation and deployment. Course includes coverage of some of the principal methods used for data mining: classification and regression trees, neural network, association rules (market basket analysis), and clustering. The course will use specialized data mining software to implement steps involved in the data mining process. The course will involve both supervised and unsupervised learning. Students are required to complete a case study using specialized DM software to capture the salient data mining principles covered in the course. Students will learn how to use specialized data mining software in the course.
Prerequisite(s)/Course Notes:
IT 14 and QM 122 or approval of department chairperson.
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