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  • Year 10
  • AQA

Machine learning engines

I can explore a range of machine learning engines which are used to build AI models.

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View unit
Lesson 1 of 1
New
New
  • Year 10
  • AQA

Machine learning engines

I can explore a range of machine learning engines which are used to build AI models.

Download all resources
Share activities with pupils

These resources will be removed by end of Summer Term 2025.

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These resources were created for remote use during the pandemic and are not designed for classroom teaching.

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Lesson details

Key learning points

  1. The engines of machine learning are the data structures and algorithms that are used to create a model.
  2. The engine you choose will depend on the nature of the problem you want to solve and the characteristics of your data.
  3. A decision tree is a supervised machine learning algorithm.
  4. Machine learning developers use decision trees to structure a set of conditions, which can be used to make predictions.
  5. A neural network is a type of machine learning model inspired by the human brain.

Keywords

  • Decision tree - a type of ML engine that makes predictions by splitting data into branches using conditions

  • Neural network - a type of ML engine consisting of interconnected nodes, organised in layers, that is trained to find patterns in data

  • Image generator - an AI tool that produces pictures from a prompt using patterns it has identified in large collections of existing images

Common misconception

Neural networks offer transparency in terms of the decisions made by the algorithm.

It’s often hard to understand why a neural network made a particular decision which makes transparency difficult.


To help you plan your year 10 computer science lesson on: Machine learning engines, download all teaching resources for free and adapt to suit your pupils' needs...

Encourage students to look closely at AI-generated images for signs of bias or misrepresentation, such as missing diversity or inaccurate depictions of certain groups. Discuss how these issues can arise from the training data.
Teacher tip

Equipment

It would be useful for learners to have access to an AI image generator application for this lesson.

Licence

This content is © Oak National Academy Limited (2025), licensed on Open Government Licence version 3.0 except where otherwise stated. See Oak's terms & conditions (Collection 2).

Lesson video

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Prior knowledge starter quiz

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6 Questions

Q1.
What does it mean when data is assigned to a “class” in machine learning?

It is given a random number.
It is made into a picture.
Correct answer: It is sorted into a predefined group.
It is erased from the system.

Q2.
What is the term for the information attached to each piece of data that tells a machine learning model which group it belongs to?

Correct Answer: label

Q3.
Why are labels important when training a classification model?

They make the data more colourful.
They speed up the computer.
Correct answer: They tell the model what the correct group is for each example.
They reduce the amount of data needed.

Q4.
Which of these is a real-world example of classification in AI?

Correct answer: sorting emails into “important” and “not important” folders
calculating the total cost of shopping
adding up exam scores
drawing a picture

Q5.
Match each keyword to its correct definition.

Correct Answer:class,a group used to organise data

a group used to organise data

Correct Answer:label,information about which group data belongs to

information about which group data belongs to

Correct Answer:classification,the process of sorting data into groups

the process of sorting data into groups

Correct Answer:category,another word for group

another word for group

Q6.
Arrange these actions for using classification in an AI system.

1 - Receive new data.
2 - Use the trained model.
3 - Assign the data to a class.
4 - Store the results.

Assessment exit quiz

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6 Questions

Q1.
What is the main function of a machine learning engine?

Correct answer: to create and train models that can solve problems using data
to store passwords
to play music
to design websites

Q2.
Put these steps in order for using a decision tree.

1 - Identify the conditions for splitting data.
2 - Split the data into branches.
3 - Follow the branches to reach a prediction.
4 - Make a final decision based on the path taken.

Q3.
Which statement about neural networks and transparency is correct?

Neural networks always make decisions that are easy to understand.
Neural networks are inspired by decision trees.
Correct answer: It can be difficult to explain why a neural network made a certain decision.
Neural networks never make mistakes.

Q4.
What is a neural network inspired by?

a tree
a calculator
Correct answer: the human brain
the internet

Q5.
Which statement about neural networks is true?

Their decisions are always easy to explain.
They are inspired by trees.
They only work with numbers.
Correct answer: They can learn complex patterns in data.

Q6.
What is the term for when a machine learning model performs very well on its training data but fails to generalise to new, unseen data?

Correct Answer: overfitting