IB Computer Science 2027 – A4.3.2 Classification: k-NN and trees – Lesson & Worksheet

IB Computer Science 2027 – A4 Machine Learning – Complete Bundle (17 lessons)

A complete, ready-to-teach bundle for **IB Computer Science (first assessment 2027)**: Machine learning, in 17 bespoke lessons written for the new syllabus. Every lesson comes with: - **Editable PowerPoint slides** – goals, starter, explanations, worked examples, a task and an exit ticket, with teacher notes - **Student worksheet (Word)** – structured questions that build from recall to exam-style application - **Answer sheet (Word)** – full model answers for quick marking or self-assessment Worth £84.83 if bought lesson by lesson. ## What's inside **A4.1 Machine learning fundamentals** - A4.1.1 Machine learning approaches - A4.1.2 Hardware for machine learning **A4.2 Data preprocessing** *(HL only)* - A4.2.1 Data cleaning - A4.2.2 Feature selection - A4.2.3 Dimensionality reduction **A4.3 Machine learning approaches** - A4.3.1 Linear regression - A4.3.2 Classification: k-NN and trees - A4.3.3 Evaluating and tuning models - A4.3.4 Clustering - A4.3.5 Association rule learning - A4.3.6 Reinforcement learning *(HL)* - A4.3.7 Genetic algorithms *(HL)* - A4.3.8 Artificial neural networks *(HL)* - A4.3.9 Convolutional neural networks *(HL)* - A4.3.10 Choosing an ML model **A4.4 Ethical considerations** - A4.4.1 Ethics of machine learning - A4.4.2 Ethics of emerging technologies ## Why teachers use it - Mapped code by code to the 2027 IB CS guide, so coverage is easy to track - SL and HL content clearly labelled - Fully editable – adapt to your class, timings and school template - Works for teaching, revision, cover lessons and homework