A complete, no-prep, single-topic worksheet on machine learning for secondary students, labelled as enrichment beyond the core GCSE specification. Students learn what machine learning is, how supervised learning uses labelled examples for classification and regression, how unsupervised learning finds patterns and clusters with no labels, the five steps of training and testing a model, and the problems that make a model fail — overfitting, biased data, and too little data. Includes guided and independent practice, four check-your-understanding questions, and an extension page that asks students to design a book-recommendation model for a school library, spot bias in a hiring model, and argue whether a self-driving car should be trusted — plus a full answer key, so marking takes minutes or students can self-mark. Links to the GCSE course are flagged throughout: a trained model is still a program that follows rules, and biased data is an ethical issue as well as a technical one. Print pages 2–3 for the class. 30–40 minutes, no equipment needed. Ideal for a cover lesson, homework, an AI enrichment session, or targeted revision of how AI works.