Logistic Regression with R: Build & Predict

Learners completing this course will be able to differentiate regression and classification tasks, apply logistic regression models in R, preprocess raw datasets, evaluate models using confusion matrices, and optimize performance through ROC curves, AUC, and threshold adjustments. They will also gain hands-on experience with real-world applications in healthcare and finance, including diabetes prediction and credit risk assessment. This course provides a step-by-step approach to mastering logistic regression, starting with foundational concepts and progressing to advanced applications. Learne…