Advanced Computer Science (Artificial Intelligence) MSc

You will study 180 credits in total during your Advanced Computer Science (Artificial Intelligence) 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 2021/21. If you are starting in September 2021, these will give you a flavour of the modules you are likely to study. All modules are subject to change.

Compulsory modules

MSc project - 60 credits
You will undertake a research project during the summer months.

Recent projects include:

  • Ontology-enriched access to digital repositories
  • Relevance and trust in social computing for decision-making
  • Advanced GIS functionality for animal habitat analysis.

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.

Artificial Intelligence - 15 credits
The module introduces the field of Artificial Intelligence (AI), taking a strongly integrative and state of the art approach based on deep neural networks. In line with the use of AI in key sectors (e.g. finance, health, law), there is an emphasis on the combination of multiple input modalities – specifically, combining images, text and structured data. Students gain hands-on experience in developing AI systems to address real-world problems, providing the knowledge and skills necessary to develop an AI system as part of an MSc project.

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.

Advanced Software Engineering - 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.

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.

Data Mining and Text Analytics - 15 credits
Introduction to linguistic theory and terminology. 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.

Scientific Computation - 15 credits
Understand the range of problems that can be formulated as nonlinear equation systems.Consider standard algorithms for these problems and the efficiency of their implementation.Demonstrate how state-of-the-art algorithms deliver gains in efficiency and allow the solution of large, sparse systems of nonlinear equations.

The full list of module information can be read in the course catalogue.