Master Decision Trees in R: Build, Predict & Evaluate

By the end of this course, learners will build, interpret, and evaluate decision tree models in R for both classification and regression tasks. They will gain hands-on skills in data preprocessing, feature engineering, and model training, while applying predictive techniques to real-world datasets including advertisements, diabetes outcomes, Caeseats sales, and bank loan defaults. Through step-by-step coding practices, learners will implement decision tree algorithms using R packages like rpart and tree, visualize results, and evaluate performance with tools such as the confusion matrix. They…