Applied Predictive Analytics

Introduces predictive analytics with applications in engineering, business, and econometrics. Topics include data preprocessing, predictive modeling with various regression and classification models (e.g., linear, logistic regression, tree-based methods, SVM, neural networks, etc.), time series analysis, and case studies. Provides a foundation of basic theory and methodology with applied examples to analyze large engineering, business, and econometric data for predictive decision making. Hands-on experiments with R will be emphasized. Offered by Systems Engr & Operations Rsch. May not be repeated for credit. Equivalent to SYST 568.