IT 531: Data Analytics

IT 531

Data Analytics initially covers the basics of big data, analytics process model, data collection, sampling, and preprocessing. It then covers predictive analytics techniques (e.g., linear regression, logistic regression, decision trees, support vector machines), descriptive analytics techniques (association rules, sequence rules, segmentation), survival analysis (measurements, Kaplan-Meier analysis, parametric survival analysis), social networks analysis (metrics, relational neighbor classifier, relational neighbor classifier, collective inference), benchmarking and data quality, and applications of analytics techniques in several commonly used applications.

Prerequisite: IT 510