Teaching about AI

AI in education: Teaching AI concepts and problem-solving with AI

This course will help you build confidence to teach about AI in structured, accurate, and accessible ways, and to support learners as they explore using AI systems to solve real-world problems.

Module 1: Start teaching about AI

In module 1, you will focus on how to start teaching about AI. You will review frameworks and resources you can use to plan balanced learning activities, and practise explaining AI concepts accurately while avoiding misconceptions (inaccurate beliefs or understandings). You will also investigate ways to make abstract AI concepts easier to understand, including unplugged activities (that learners complete without digital devices), examples, and analogies.

Module 2: Solving problems using AI

In module 2, you will focus on helping learners investigate how people use AI systems to solve real-world problems. You will review the AI project lifecycle and consider how to guide learners through each stage, starting with identifying and clearly defining problems that may suit AI-driven solutions. You will also examine how developers collect and prepare data, train and test models, evaluate performance, and improve AI systems over time.

Throughout this module, you will consider approaches, resources, and activities you could use to help learners define problems, plan and evaluate potential solutions, and think critically about the role AI technologies can play in solving problems.

Required knowledge or skills

You will need a basic understanding of what data-driven AI systems are and how they work, machine learning, and common AI-related terms, like 'AI model' and 'training'. If these ideas are new to you, we recommend that you complete our free Introducing AI course first.

What you will learn

After completing these two modules, you will be able to:

• Plan structured learning activities that help learners understand AI concepts
• Choose teaching strategies that make AI concepts accessible and support accurate mental models
• Evaluate and adapt AI teaching approaches and resources to suit your learners and context
• Identify and use real-world examples to help learners understand what kinds of problems AI technologies can help solve
• Explain how developers design, test, and improve AI systems, including the role of data in training and evaluation
• Guide learners through the AI project lifecycle, helping them define problems, plan solutions, and evaluate improvements