Course Overview

This course provides a working knowledge of applied predictive modeling. Students will obtain a broad understanding of model training, evaluations, and development procedures with a wide variety of applications to real-world problems. This course introduces best practices for managing data science projects and presenting analytical results to technical and non-technical audiences. Course topics include linear and non-linear regression modeling methods, linear and non-linear classification modeling methods, model selection, variable importance, variable selection and model applications, code, and R package management using RStudio. Prerequisites: ADS 501 and ADS 502

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