This data science session provided an in-depth understanding of the different types of Machine Learning: supervised, unsupervised, and reinforcement learning. Attendees learned how supervised learning used labeled data for predictive tasks like classification and regression, how unsupervised learning identified patterns in unlabeled data for clustering and dimensionality reduction, and how reinforcement learning involved agents learning from interactions with their environment to maximize rewards. The session also included practical examples and applications in real-world scenarios, making it suitable for beginners and those curious about machine learning's role in data science.