You will study 180 credits in total during your Advanced Computer Science MSc. A standard module is typically worth 15 credits and the research project is worth 60 credits. These are the modules relating to this programme of study for academic year 2021/22. If you are starting in September 2022, these will give you a flavour of the modules you are likely to study. All modules are subject to change.
MSc Project - 60 credits
You will undertake a research project during the summer months.
Recent examples include:
- iPad interaction for wall-sized displays
- Modelling the effects of feature-based attention in the visual cortex
- Energy-efficient cloud computing.
Optional modules include:
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.
Knowledge Representation and Reasoning - 15 credits
Analysing descriptions of complex real world scenarios in terms of formal representation languages. Understanding automated reasoning and ontology as well as their applications.
Data Mining and Text Analytics - 15 credits
Understand and use algorithms and resources for implementing .and evaluating text mining and analytics systems. Develop solutions using open-source and commercial toolkits. Consider the applications of data mining and text analytics through case studies in information retrieval and extraction.
Machine Learning - 15 credits
This module covers topics including neural networks, decision trees, support vector machines, Bayesian learning, instance-based learning, linear regression, clustering, reinforcement learning, deep learning and methods for evaluating performance.