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.
4,051 enrolled on this course
Duration
4 weeksWeekly study
2 hours100% online
How it works
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
When would you like to start?
Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.
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 Scratch, Machine Learning for Kids, and Teachable Machine websites.
One of these tasks will also require the use of a webcam.
Who developed the course?
Comments
Post a Comment