Unit of lessons
Our set of lessons provides everything you need, including lesson plans, presentations, videos, and worksheets.
Unit overview
Updated: 25 Oct 23
Learning graph
Updated: 31 Mar 23
AI glossary of terms
Updated: 18 Apr 23
Lesson 1: What is AI?
In this lesson, students will explore the current state of artificial intelligence (AI) and how it is used in the world around them. They will look at the differences between rule-based and data-driven approaches to programming, and they will consider the benefits that AI applications could bring to society, as well as any negative consequences that their use could lead to.
Lesson 2: How computers learn from data
In this lesson, students will focus on the role of data-driven models in AI systems. They will be introduced to machine learning and learn about three common approaches to creating models. Finally, they will explore classification, a specific application of machine learning.
Lesson 3: Bias in bias out
In this lesson, students will create their own machine learning model to classify images of apples and tomatoes. They will discover that a limited data set can lead to a flawed ML model. They will then explore how bias can appear in a data set, leading to ML models producing biased predictions.
Lesson 4: Decision trees
In this lesson, students will take their first in-depth look at a type of model: decision trees. Students will see how different training data results in the creation of different models, experiencing first-hand what it means for models to be data-driven. Finally, students will see why machine learning is used to create decision trees.
Lesson 5: Solving problems with ML models
In this lesson, students will be introduced to the AI project lifecycle and use it to create a machine learning model. They will apply a user-focused approach to working on AI projects. They will choose a project, then train a machine learning model, then test their model to determine its accuracy.
Lesson 6: Model cards and careers
In this lesson, students will finish the AI project lifecycle by creating a model card to explain their ML model. In the final activities, students will explore a range of AI-related careers. They will hear from people working in the field of AI, as well as considering how AI applications and machine learning can be used in fields they are interested in.