Linear Regression with R: Build & Optimize

By the end of this course, learners will be able to define core concepts of Linear Regression, construct simple and multiple regression models, apply dummy variable techniques, and evaluate model performance using statistical tests. Participants will also develop the ability to optimize models through backward elimination and validate predictive accuracy on new datasets. This course is designed to provide a step-by-step learning pathway from the fundamentals of regression equations to advanced applications in supervised machine learning with R. Learners will gain practical skills by working o…