Resources included (13)

Ethics of emerging technologies – IB Computer Science lesson

ML model selection and ethics – IB Computer Science lesson

Convolutional neural networks – IB Computer Science lesson

Artificial neural networks – IB Computer Science lesson

Reinforcement learning – IB Computer Science lesson

Unsupervised learning – IB Computer Science lesson

Evaluating and tuning ML models – IB Computer Science lesson

Classification: k-NN and decision trees – IB Computer Science

Linear regression – IB Computer Science lesson

Dimensionality reduction – IB Computer Science lesson

Data cleaning and feature engineering – IB Computer Science

Hardware for machine learning – IB Computer Science lesson

Machine learning approaches – IB Computer Science lesson
17 ready-to-teach lessons for IB Diploma Computer Science (first assessment 2027): Machine Learning. Every lesson has editable PowerPoint slides, a student worksheet and full answers, and the bundle costs less than buying the lessons one by one.
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 insideA4.1 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
- 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
Last updated: November 2026.
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