pptx, 331.02 KB
pptx, 331.02 KB
docx, 15.61 KB
docx, 15.61 KB
docx, 14.52 KB
docx, 14.52 KB

IB DP Computer Science A4.3.2 Supervised Learning – Classification lesson and worksheet for the new 2027 syllabus. A classroom-ready resource covering classification, labelled data and supervised machine learning.

IB Computer Science 2027 – A4.3.2 Supervised Learning – Classification

A classroom-ready lesson resource for IB Diploma Programme Computer Science, aligned with the new IB Computer Science syllabus for first assessment in May 2027.

What is included
  • Lesson presentation
  • Student worksheet
  • Classroom activities
  • Student tasks
  • Questions to check understanding
  • Mark scheme / answers
Syllabus coverage

A4.3 Machine Learning Approaches

A4.3.2 Supervised Learning – Classification

Students explore how supervised learning can be used to classify data into categories using labelled training data.

Topics include:

  • Supervised learning
  • Training data
  • Labels and features
  • Classification
  • Classification categories
  • Training and prediction
  • Real-world applications of classification
  • Examples of classification problems

Students apply their understanding to classification scenarios and consider how labelled data is used to train machine learning models.

Suitable for
  • IB Diploma Programme Computer Science
  • SL and HL
  • New 2027 syllabus
  • First assessment May 2027
  • Secondary students aged 16–18

The resource can be used as a standalone lesson or incorporated into an existing IB Computer Science scheme of work.

Please note: This is an original teaching resource and is not affiliated with or endorsed by the International Baccalaureate Organisation.

Get this resource as part of a bundle and save up to 54%

A bundle is a package of resources grouped together to teach a particular topic, or a series of lessons, in one place.

Bundle

IB Computer Science 2027 – A4 Machine Learning – Complete Lesson & Worksheet Bundle

IB DP Computer Science Topic A4 Machine Learning complete lesson and worksheet bundle for the new 2027 syllabus. A comprehensive collection of classroom-ready resources covering machine learning fundamentals, data preprocessing, machine learning approaches and ethical considerations. ## IB Computer Science 2027 – A4 Machine Learning A complete teaching bundle for **IB Diploma Programme Computer Science**, aligned with the **new IB Computer Science syllabus for first assessment in May 2027**. This bundle brings together the full set of Topic A4 Machine Learning lesson resources, providing a structured collection of presentations, worksheets, activities and answers. ### What is included - Lesson presentations - Student worksheets - Classroom activities - Student tasks - Questions to check understanding - Mark schemes / answers ### Syllabus coverage **A4.1 Machine Learning Fundamentals** - A4.1.1 Types of Machine Learning - A4.1.2 Hardware Required for Machine Learning **A4.2 Data Preprocessing – HL only** - A4.2.1 / A4.2.2 Data Cleaning & Feature Engineering - A4.2.3 Dimensionality Reduction **A4.3 Machine Learning Approaches** - A4.3.1 Linear Regression - A4.3.2 Supervised Learning – Classification - A4.3.3 Model Evaluation & Hyperparameters - A4.3.4 / A4.3.5 Unsupervised Learning - A4.3.6 / A4.3.7 Reinforcement Learning - A4.3.8 Artificial Neural Networks - A4.3.9 Convolutional Neural Networks - A4.3.10 Model Selection & Comparison **A4.4 Ethical Considerations** - A4.4.1 / A4.4.2 Ethics of Emerging Technologies ### Suitable for - **IB Diploma Programme Computer Science** - **SL and HL** - **New 2027 syllabus** - **First assessment May 2027** - **Secondary students aged 16–18** This bundle provides a complete set of teaching resources for Topic A4 and can be used as the foundation of an entire Machine Learning unit. --- **Please note:** These are original teaching resources and are not affiliated with or endorsed by the International Baccalaureate Organisation.

£29.99

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