How Machines Learn to Spot Patterns in Data (Teach This Topic)

This plan supports teaching the completed lesson about how machine-learning systems use examples to find statistical patterns and make predictions or groupings. It follows the lesson sequence with practical questions, simple paper activities, checks for understanding and adaptations for different learners. By the end, learners should understand the roles of data, features, labels, algorithms, models, training and testing, while recognising uncertainty, overfitting, bias and the difference between correlation and causation.