Machine Learning and Data Mining

In this unit, you will explore key concepts in machine learning (ML) and data mining, including supervised and unsupervised learning, classification, regression, clustering, and association rules. You will apply classic techniques to real-world problems across various industries, using AI-assisted tools like Copilot for code generation and optimisation. Through hands-on exercises, you will implement and apply core ML algorithms to solve complex data challenges. You are expected to think critically, analyse results, and derive actionable insights. By the end of the unit, you will be able to design, implement, and evaluate machine learning solutions, preparing you for roles in data science, AI development, or further study in intelligent systems.

Learning Outcomes

On successful completion of this unit, students will be able to:

1. Evaluate key machine learning algorithms and data mining techniques, and their applications in real-world scenarios;
2. Apply supervised and unsupervised learning methods, including classification, regression, clustering, and association rule mining, to solve practical data problems;
3. Evaluate the performance of machine learning models using appropriate metrics and optimise model selection for different data-driven tasks;
4. Develop machine learning models and workflows using AI-assisted tools individually and as part of a team;
5. Analyse ethics and data privacy in machine learning and data mining.