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CSCD 409: Data Mining & Warehousing

Credits: 3

Introduction to data mining and motivating challenges. Types of data, measures of similarity and distance. Data exploration and warehousing. Supervised learning. Bias and variance. Classification techniques and their evaluation. Clustering. Association and sequence rule mining.

This course will apply computing principles, probability and statistics relevant to the data mining discipline to analyze data.  A thorough understanding of model programming with data mining tools, algorithms for estimation, prediction, and pattern discovery. Analyze a problem, identifying and defining the computing requirements appropriate to its solution: data collection and preparation, functional requirements, selection of models and prediction algorithms, software, and performance evaluation