Course Overview
This course provides a working knowledge of applied predictive modeling. Students will obtain a broad understanding of model training and development procedures, applications to real-world business problems, the differences between predictive model types and uses, and introduce best practices to manage data science projects, create web applications, and present results to technical and non-technical audiences. Course topics include linear and non-linear regression modeling methods, linear and nonlinear classification modeling methods, model selection, variable importance, variable selection and model applications, code and R package management, and web application development using RStudio and R Shiny.