This course introduces students to the fundamentals of Machine Learning, a branch of AI (Artificial Intelligence) behind technologies such as voice assistants, image recognition, and self-driving vehicles.

Students will explore how machine learning systems are created by collecting and preparing data, training a model, testing its accuracy, and then using the trained model to make predictions or recognise patterns.

Through practical activities and projects, students will train their own machine learning models and use them to create interactive applications. Along the way, they will learn about the importance of good training data, discover why AI systems sometimes make mistakes, and explore how the quality and fairness of data can affect the results produced by AI.

No previous experience with Artificial Intelligence or Machine Learning is required.

By the end of the course students should have a basic understanding of what machine learning is, where it used and how to use a it.

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