Study Guides

Unit Summary

This unit introduces pupils to the emerging field of data science. They will explore what AI systems are and the different categories of AI. The concept of machine learning and how models are driven by data will be explored. They will also consider the ethical and wider implications of AI systems.

Lesson Summary

You will learn to explain how AI systems classify data into categories and how classification underpins many AI tasks.

Key Notes

• Classification is a type of ML task where an AI system assigns data into predefined categories or "classes".
• The AI classification system is trained on labelled data.
• Classification is one of the most fundamental tasks in AI and underpins many real world systems.

Vocabulary To Learn

• class: a predefined group used to organise data that machine learning (ML) developers use to train classification models
• label: each piece of data is annotated with one or more labels which provide information about that data

Common Mistakes To Avoid

• A classifier can be improved by providing more training data.

3 Quick Questions (With Answers)

More Lessons In This Unit

• Approaches to training machine learning models Study Guide
• Data driven models Study Guide
• Introduction to AI Study Guide
• Machine learning Study Guide
• Machine learning engines Study Guide
• Predictive vs generative AI Study Guide
• Social and ethical issues of AI systems Study Guide