A subset of artificial intelligence (AI), machine learning uses data and algorithms to imitate the way that humans learn. While simple rule-based automation is typically used for standardised and predictable processes, machine learning can handle more complex processes. They are also able to learn and improve from experience without being explicitly programmed, leading to greater improvements in accuracy and efficiency. 

In the competitive business landscape of today, machine learning is an increasingly powerful tool in helping organisations enhance their workflows through automation. By taking straightforward automated tasks and layering them in an element of prediction, it can help to solve problems at a speed and scale that cannot be duplicated by human efforts alone. Established cases of machine learning in the industries include fraud detection, medical diagnosis and e-commerce recommendation models. 

This introductory course in machine learning covers fundamental concepts, algorithms and techniques. Learners will learn how to uncover patterns to derive actionable insights. They can also expect engaging hands-on workshops to help them reinforce understanding of the subject matter. As a concluding team project, learners will work as a group to create and train a Neural Network model to classify images.