COMP4030: Data Science and Machine Learning

Teaching team

Core ideas of the module

An opinionated introduction to the core challenges of data science and machine learning.

This module will enable you to appreciate the range of data analysis problems that can be modelled computationally and a range of techniques that are suitable to analyse and solve those problems. Topics covered include: basic statistics; types of data; data visualisation techniques; data modelling; data pre-processing methods including data imputation; forecasting methods; clustering and classification methods (decision trees, naīve bayes classifiers, k-nearest neighbours); data simulation and model interpretation techniques to aid decision support.


Other reading