Machine Learning Unplugged
Explore machine learning and design a basic model
Secondary and FE
7 sessions
Unplugged activities
No programming required
Course Summary
- Students explore a range of machine learning applications
- They consider the social, practical and ethical aspects of machine learning
- Students then identify a real life problem they care about -- Students can work individually or in teams to design a machine learning model to solve the problem they have identified
- Course can be delivered in a standard classroom without access to laptops/computers
- Course includes facial recognition, chatbots, recommendatio and decision systems, self driving cars, bias in machine learning algorithms, impact on employment
Course sessions
Login or sign up now to access all of the sessions
- Session 1: What is machine learning
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Session 2: Facial Recognition
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Session 3: Natural Language Processing
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Session 4: Recommendation Systems
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Session 5: Decisions and Ethics
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Session 6: Putting it all together
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Session 7: Designing your own model
Core resource
Student Workbook
- Printable student A4 workbook containing practical activities
- Guides you and your students through the course
- Fully editable, making it easy for you to adapt to meet your needs
Core resource
Scheme of Work
Get a quick overview of the course structure Review the learning objectives and outcomes for each session
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Session 1
What is machine learning
Learning objectives
Core
- Understand what machine learning is
- Understand how machines learn
Challenge
- Understand how machines learn to identify images
- Understand what neural networks are
Go to session
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Session 2
Facial Recognition
Learning objectives
Core
- Understand how facial recognition works
- Understand some of the uses of facial recognition
Challenge
- Understand some of the issues surrounding facial recognition
- Understand how there can be bias in facial recognition
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Session 3
Natural Language Processing
Learning objectives
Core
- Understand what a chatbot is
- Understand how to build a natural language recognition prototype
Challenge
- Recognise the advantages of natural language processing
- Appreciate real life applications of chatbots
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Session 4
Recommendation Systems
Learning objectives
Core
- Understand how machine learning can be used to make recommendations
- Understand what a filter bubble is
Challenge
- Understand the potential dangers of recommendation systems
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Session 5
Decisions and Ethics
Learning objectives
Core
- Understand how machine learning is used to make decisions
- Understand potential issues with the application of machine learning
Challenge
- Be able to evaluate the impact of ethical considerations in the application of machine learning
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Session 6
Putting it all together
Learning objectives
Core
- Understand the potential impact of machine learning on employment and careers
- Be able to summarise your learning in a written report
Challenge
- Be able to express your views clearly
- Be able to evaluate the impact of machine learning across a range of different applications
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Session 7
Designing your own model
Learning objectives
Core
- Identify everyday problems which could be solved using machine learning
- Gain a better understanding of the data requirements of your machine learning idea
Challenge
- Be able to convey your ideas clearly and concisely
- Be able to critically evaluate machine learning ideas and select the strongest to take forward