modules

This module will improve your knowledge and skills in machine learning and data science. You will gain theoretical and practical understanding of some of the core techniques in machine learning (including supervised/unsupervised methods, feature extraction, binary classification, elementary text and image analysis, amongst others). You will also understand how machine learning and other techniques are combined in effective data science workflows, alongside some of the practical challenges faced in real-world data science, such as handling missing or erroneous data, linking different datasets, and data visualisation.

Pre-requisites: COM1011 Fundamentals of Machine Learning, ECM1400 , ECM1410 , MTH1002 , MTH1004 , or equivalent

Co-requisites: MTH2006

This module is suitable for students with sufficient preparation in Mathematics and Programming.

_{Please note that all modules are subject to change, please get in touch if you have any questions about this module.}