You will study 180 credits in total during your Advanced Computer Science (Data Analytics) MSc. These are the modules studied in 2021/22 and will give you a flavour of the modules you are likely to study in 2022/23. All modules are subject to change.
Recent projects include:
- Text mining of e-health patient records
- Java-based visualisation on ultra-high resolution displays
- Data mining of sports performance data.
Machine learning - 15 credits
Topics selected from: Decision trees, Bayesian networks, instance-based learning, kernel machines, clustering, reinforcement learning inductive logic programming, artificial neural networks, deep learning.
Big Data Systems - 15 credits
The aim of the module is for students to develop a practical understanding of methods, techniques and architectures needed to build big data systems required, so that knowledge may be extracted from large heterogeneous data sets.
Data Science - 15 credits
The aim of the module is for students to understand methods of analysis that allow people to gain insights from complex data. The module covers the theoretical basis of a variety of approaches, placed into a practical context using different application domains.
Optional modules include:
Knowledge Representation and Reasoning - 15 credits
The principal representations and algorithms used in machine learning and the techniques used to evaluate their performance. You will implement a challenging learning system using a publicly available pack of standard algorithms.
Data Mining and Text Analytics - 15 credits
Introduction to data and text theory and terminology. Tools and techniques for data-mining and text processing, focusing on applied and corpus-based problems such as data classification by Machine Learning classifiers, collocation and co-occurrence discovery and text analytics. Open-source and commercial text mining and text analytics toolkits. Web-based text analytics.
Cloud Computing - 15 credits
State-of-the-art approaches and solution strategies for designing, building and maintaining cloud applications. This module covers areas such as programming models, virtualisation and quality of service.