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Introduction to Machine Learning and AI

Discover the fundamentals of machine learning, how it works, and learn to train your own AI using free online tools.

Introduction to Machine Learning and AI

Build your knowledge and skills in machine learning

From self-driving cars to determining someone’s age, artificial intelligence (AI) systems trained with machine learning (ML) are being used more and more. But what is AI, and what does machine learning actually involve?

On this four-week course from the Raspberry Pi Foundation, you’ll learn about different types of machine learning, and use online tools to train your own AI models.

You’ll delve into the problems that machine learning can help to solve, discuss how AI is changing the world, and think about the ethics of collecting data to train a machine learning model.

Explore the different types of machine learning

The first week of this course will guide you through how you can use machine learning to label data, whether to work out if a comment is positive or negative or to identify the contents of an image.

Then you’ll look at machine learning algorithms that create models to give a numerical output, such as predicting house prices based on information about the house and its surroundings.

You’ll also explore other types of machine learning that are designed to discover connections and groupings in data that humans would likely miss, giving you a deeper understanding of how machine learning can be used.

Use tools to develop and train your own AI

During this course, you’ll also investigate the different ways that the machine learning actually takes place.

You’ll compare supervised learning, which uses training data labelled with the desired outcome, to unsupervised learning, where the aim of the machine learning is to spot new connections.

In the final week of the course, you’ll investigate neural networks; a type of machine learning inspired by the structure of the brain that is used by many state-of-the-art AI systems such as YOTI’s age determination algorithm.

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Skip to 0 minutes and 3 seconds Can machines learn? If so, what can you teach them? What is artificial intelligence? This free course will introduce you to the world of machine learning and artificial intelligence, one of the most exciting areas of technological development. You will teach an algorithm to recognise hand gestures. You’ll also create a noughts and crosses game that learns as you play. And you’ll consider the impact of automation on the world around us. This 4 week course also contains peer-led discussions, trainer interaction, and practical activities to help embed your new knowledge. So whether you’re a teacher with students of your own or simply curious about the future of AI, this course will give you an introduction to machine learning and artificial intelligence.

Skip to 0 minutes and 52 seconds Sign up now at rpf.io/machinelearning.


  • Week 1

    Introduction to machine learning

    • Welcome to the course

      Meet the course team and your fellow learners, and discover what you'll be learning over the next three weeks. You will also hear from Machine Learning for Kids creator, Dale Lane.

    • What are AI and machine learning?

      Find out about the history of AI as well as identifying the differences between AI and ML and related fields.

    • Using AI for classification

      Explore the concept of classification by making your own ML application.

  • Week 2

    Solving problems using AI

    • What problems can AI solve?

      Learn about the types of problems machine learning can help solve, including classification, regression, and knowledge organisation.

    • Collecting and preparing data for machine learning

      Explore the discipline of data science and apply skills from that field by creating your own system that predicts a user's favourite type of movie.

    • Potential problems with AI

      Explore the terms bias and variance and discover the potential impact of bias in machine learning algorithms when applied to recruitment.

    • A recap of the week...

      Consolidate some of the learning you have done so far in this course by discussing the use of machine learning to estimate the age of people based on images of their faces.

  • Week 3

    How machines learn

    • The machine learning process

      All machine learning projects use the same lifecycle of repeated input, train, test stages until they are ready for deployment.

    • Supervised learning: Decision trees and nearest neighbour

      Supervised learning is one of the most common forms of machine learning, using labelled data to train an algorithm to map inputs to desired outputs.

    • Unsupervised and reinforcement learning

      Unlike the machine learning methods you've encountered so far, unsupervised and reinforcement learning both work without you having to provide labels.

    • End of Week 3

      Examine how machine learning will impact the cybersecurity industry.

  • Week 4

    Neural networks and more activities

    • Welcome to week 4

      Find what you will learn this week, and reflect on the learning you have done so far on the course.

    • How neural networks work

      Neural networks emulate the way the cells in the brain communicate and work together to learn.

    • Activities for learning

      There are many different ways to communicate machine learning concepts to the people around you, whether as a pen and paper "unplugged" activity, a practical example or a case study on someone working in the industry.

    • Writing a machine learning resource

      To help you share your new found knowledge, you are going to create a resource to communicate one of the machine learning concepts you have picked up in this course.

    • Further steps

      Discover the next steps you can take to continue your learning journey with AI and machine learning.

When would you like to start?

Start straight away and learn at your own pace. If the course hasn’t started yet you’ll see the future date listed below.

Learning on this course

If you'd like to take part while our educators are leading the course, they'll be joining the discussions, in the comments, between these dates:

  • 4 Oct 2021 - 29 Oct 2021

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Demonstrate several working machine learning models
  • Explain the different types of machine learning, and the problems that they are suitable for
  • Compare supervised, unsupervised, and reinforcement learning
  • Discuss the ethical issues surrounding machine learning and AI

Who is the course for?

This course is designed for anyone looking to learn more about machine learning without having to understand the maths involved.

To get the most out of this course, you should already have an understanding of what a computer algorithm is.

Some of the practical tasks also require familiarity with the Scratch programming language.

What software or tools do you need?

The practical tasks in this course require access to the Scratch, Machine Learning for Kids, and Teachable Machine websites.

One of these tasks will also require the use of a webcam.

Who will you learn with?

I lead the Raspberry Pi Foundation's efforts to support educators with resources and training. I'm an experienced computing teacher, an advocate for diversity in tech, author and a YouTuber.

Ben is a Learning Manager for the Raspberry Pi Foundation making teaching resources for educators. When he's not spending time tinkering with his Raspberry Pi, he likes spending time with his family

Who developed the course?

Raspberry Pi Foundation

The Raspberry Pi Foundation works to put the power of digital making into the hands of people all over the world, so they are capable of understanding and shaping our increasingly digital world.

Learning on FutureLearn

Your learning, your rules

  • Courses are split into weeks, activities, and steps, but you can complete them as quickly or slowly as you like
  • Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
  • Stay motivated by using the Progress page to keep track of your step completion and assessment scores

Join a global classroom

  • Experience the power of social learning, and get inspired by an international network of learners
  • Share ideas with your peers and course educators on every step of the course
  • Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others

Map your progress

  • As you work through the course, use notifications and the Progress page to guide your learning
  • Whenever you’re ready, mark each step as complete, you’re in control
  • Complete 90% of course steps and all of the assessments to earn your certificate

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