Supervised learning is a type of machine learning where an algorithm learns from labeled training data, and makes predictions based on that data. Coursera's supervised learning catalogue teaches you to construct predictive models, understand the principles of machine learning algorithms, and apply them to real-world problems. You'll learn about various supervised learning techniques such as linear regression, K-nearest neighbors, support vector machines and decision trees. Additionally, you'll gain insights into concepts like overfitting, underfitting, bias-variance tradeoffs, and cross-validation. This knowledge will be invaluable whether you're aiming to become a data scientist, machine learning engineer, or simply want to understand the technology driving today's artificial intelligence advancements.