Rutgers University 3 credits Economics
Data mining is a process used by many companies in various industries to turn raw data into decision-making information. Applied Data Mining introduces students to how to apply data mining algorithms, supervised and unsupervised, to discover patterns hidden in the data. This class builds on the statistical foundations and aims to equip students with data analytics skills. The major mining algorithms including Naïve Bayes, Support Vector Machine, Regression Trees, Probit/Logit Modeling, K-Means Clustering, and Social Network Analysis, etc., will be fully explained. Students will be trained to apply various mining algorithms using real data derived from various disciplines. Prerequisite: 50:220:222 or 50:960:283 or 50:830:250 or permission of instructor.
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