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.

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.

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.

• Introduction to machine learning
• Welcome to the course
• What are AI and machine learning?
• Using ML for classification
• Solving problems using AI
• What problems can AI solve?
• Collecting and preparing data for machine learning
• Potential problems with AI
• A recap of the week...
• How machines learn
• The machine learning process
• Supervised learning: Decision trees and nearest neighbour
• Unsupervised and reinforcement learning
• End of Week 3
• Neural networks and more activities
• Welcome to Week 4
• How neural networks work
• Activities for learning
• Writing a machine learning resource
• Further steps