Module overview
Machine learning is transforming engineering by enabling systems to learn from data, identify complex patterns and make intelligent predictions. From autonomous vehicles and predictive maintenance to medical diagnosis and smart manufacturing, these techniques are becoming an essential part of modern engineering practice. This module introduces the fundamental principles of machine learning from an engineering perspective, equipping you with the knowledge and practical skills to apply these powerful tools to real-world challenges.
You will explore the mathematical and statistical concepts that underpin modern machine learning before developing and implementing algorithms to analyse complex engineering datasets. Through practical examples and hands-on computational activities, you will learn how to prepare data, select appropriate machine learning techniques, evaluate model performance and interpret results critically. Along the way, you will develop an appreciation of both the capabilities and limitations of machine learning, enabling you to apply these methods responsibly and effectively within engineering applications.
By the end of the module, you will be able to develop and evaluate machine learning solutions for engineering problems, combining computational, analytical and critical thinking skills that are increasingly sought across industries including manufacturing, healthcare, energy, robotics and autonomous systems.