This module introduces the fundamental principles and techniques of classical machine learning, with an emphasis on statistical approaches to learning from data. It explores how models capture patterns, make predictions, and generalise through both statistical and non-statistical methods, including regression, classification, clustering, and ensemble techniques. Students develop practical intuition and conceptual understanding of how different learning paradigms operate, preparing them to analyse and interpret model behaviour across diverse data-driven contexts.

Detailed Description

Full programme information can be found in the Module and Programme Catalogue

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