This 1-hour session introduces key concepts of clustering and classification, two fundamental techniques in data analysis and machine learning. Participants will explore the differences between supervised and unsupervised learning, understand how algorithms group data or assign class labels, and see practical examples of real-world applications. The session will include a brief theoretical overview followed by an interactive discussion of use cases, highlighting strengths, limitations, and best practices.