Data scientific methods and techniques for uncovering information from web user behavior. Topics may include web log cleaning and filtering, server identification, feature derivation, bot identification, de-spidering, user identification, heuristic methods, error handling, session identification, path completion, explaining why users leave the website, identifying anomalous user behavior, basket transformations, estimating last-page duration, exploratory data analysis and modeling for web analytics, including clustering, association, and classification. 

Prerequisites: DATA 511 or permission of department chair.

4 Credits

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