An Overview of Artificial Intelligence and Machine Learning

An Overview of Artificial Intelligence and Machine Learning


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

An image representing elements of the course, including an email being labelled as SPAM due to highlighted words, representations of neural networks and clustering, and a robot attempting to classfiy an alien as a rock or not a rock

Find out more about how to join this course

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.

What topics will you cover?

  • Classification and making predictions
  • Data Science and Machine Learning
  • Supervised and unsupervised learning
  • Neural networks
  • Ethics and Machine Learning

Learning on this course

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 ScratchMachine Learning for Kids, and Teachable Machine websites.

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

Who will you learn with?

Carrie Anne Philbin

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.

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