Classification
Lesson details
Learning outcome
I can explain how AI systems classify data into categories and how classification underpins many AI tasks.
Key learning points
- 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.
Keywords
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 misconception
A classifier can be improved by providing more training data.
More data doesn't always mean improved predictions. The quality of data provided to a classifier is as important as the quantity.
Teacher tip
Pupils will probably have come across classifiers, so perhaps lead a classroom discussion about where they may have seen AI classification in real world scenarios.
Licence
Lesson video
Loading...
Prior knowledge starter quiz
6 Questions
Q1.What is a key feature of supervised learning?
Q2.Which of the following is most likely to use unsupervised learning?
Q3.What kind of data does unsupervised learning use?
Q4.What is the main goal of clustering in machine learning?
Q5.Arrange these actions for using clustering in unsupervised learning.
Q6.Match each keyword to its correct definition.
training a model with labelled data
training a model with unlabelled data
sorting data into pre-set categories
grouping data points based on similarities
Assessment exit quiz
6 Questions
Q1.What is the machine learning task called where data is assigned to predefined categories or groups?
Q2.Match each keyword to its correct definition.
a predefined group used to organise data
information about which category a data point belongs to
the process of sorting data into categories
a machine learning model that assigns data to categories
Q3.What is one reason a classifier might make mistakes?
Q4.Why is classification important in AI systems?
Q5.Which of the following is not a classification task?
Q6.Arrange these steps into the correct order to create a good classifier.
To help you plan your 10 computer science lesson on: Classification, download all teaching resources for free and adapt to suit your pupils' needs...
To help you plan your 10 computer science lesson on: Classification, download all teaching resources for free and adapt to suit your pupils' needs.
The starter quiz will activate and check your pupils' prior knowledge, with versions available both with and without answers in PDF format.
We use learning cycles to break down learning into key concepts or ideas linked to the learning outcome. Each learning cycle features explanations with checks for understanding and practice tasks with feedback. All of this is found in our slide decks, ready for you to download and edit. The practice tasks are also available as printable worksheets and some lessons have additional materials with extra material you might need for teaching the lesson.
The assessment exit quiz will test your pupils' understanding of the key learning points.
Our video is a tool for planning, showing how other teachers might teach the lesson, offering helpful tips, modelled explanations and inspiration for your own delivery in the classroom. Plus, you can set it as homework or revision for pupils and keep their learning on track by sharing an online pupil version of this lesson.
Explore more key stage 4 computer science lessons from the Data science: AI and machine learning unit, dive into the full secondary computer science curriculum, or learn more about lesson planning.