In this hands-on session, we explore two of the most widely used supervised learning algorithms in data science: Decision Trees and Logistic Regression. You'll learn how Decision Trees provide interpretable rules for classification and regression tasks, and how Logistic Regression models probability for binary outcomes using a simple yet powerful approach.

We’ll compare their strengths and weaknesses, delve into practical examples, and cover best practices for model evaluation and optimization. Whether you're a beginner or brushing up on machine learning fundamentals, this session will give you the tools to build and interpret predictive models with confidence.