What you’ll study
On this Masters programme, you’ll develop the core computer science skills of computational thinking, computational problem solving and software development. Importantly, you’ll also develop specialist skills and knowledge in problem structuring, machine learning, neural networks, genetic algorithms, and data analytics, and undertake an independent artificial intelligence project.
Career opportunity and advancement
The programme will equip you for a range of in demand roles in computer science and software development. Our world-class Russell Group institution and leading Department of Computer Science offer global reach and industry-relevant content – key differentiators that set our programmes apart. The Department has a long-established and successful track record of training for industry, ensuring that our programmes remain current to the needs of modern-day employers.
- Part of the elite Russell Group of major research-intensive universities
- Ranked Top 20 in the UK (Guardian University Rankings 2021)
- Top of the Russell Group for academic support (NSS 2020)
- Over 18,000 students and 4,000 staff from 140 countries
- 16th in the Times Higher Education Europe Teaching Rankings (2019)
- 128th in the Times Higher Education World University Rankings (2020)
Artificial Intelligence and Machine Learning (15 credits)
This module explores the field of artificial intelligence along with the principal ideas and techniques in three core topic areas: problem solving, knowledge representation and machine learning. The implications of AI for business and society are also covered.
Applied AI (15 credits)
This module explores advanced AI techniques through the application and evaluation of genetic algorithms, neural networks, local search techniques and deep learning. It develops your understanding of the application areas and problems that advanced AI techniques can enhance and optimise.
Algorithms and Data Structures (15 credits)
This module provides techniques for using algorithms and associated data structures. It also covers computational thinking and the theoretical underpinnings and practical applications of computer science, covering: programming; control structures; methods; inheritance; arrays and mechanics of running and testing; complexity and implementation of algorithms in programs.
Advanced Programming (15 credits)
This module details advanced programming concepts such as file manipulation, event-driven programming, multi-threaded programming, programming for data analysis and the use of packages and documentation. It also covers the social context of computing: social impact of computers and the internet; professionalism; codes of ethics and responsible conduct; copyrights, intellectual property; and software piracy.
Computer Architecture and Operating Systems (15 credits)
The module covers the concepts of modern computer architecture and system software. After an overview of computer architecture, it then delves into how computer systems execute programs, store information, and communicate. You’ll also learn the principles, design and implementation of system software such as operating systems.
Computer and Mobile Networks (15 credits)
A sound understanding of internet architecture, protocols and technologies and their real-world applications forms the core of this module. Discussions around networks and the internet, network architecture, communication protocols and their design principles, wireless and mobile networks, network security issues and networking standards feature. The module also covers related social, privacy and copyright issues.
Software Engineering (15 credits)
This module focuses on designing and building software systems. You’ll look at principles and patterns of software design, where to apply them, and how they inform design choices. You’ll learn techniques for ensuring systems you build behave correctly. We demonstrate how the application of these principles makes it possible to evolve systems effectively and rigorously.
Big Data Analytics (15 credits)
This module provides skills in data analytics, including the preparation of data, data handling, formulating precise questions and using tools from statistics and data mining to address them.
Research Methods (15 credits)
This module provides you with a range of approaches to research and individual research projects. Formulate research questions appropriate to an area of interest, and evaluate the relationship between question, methodology and method.
Research Proposal (15 credits)
This is an extended research proposal for your final Individual Research Project. The module is created to ensure you are prepared for the IRP in sufficient depth before undertaking final studies. Designed to give you the flexibility of developing a proposal, it explores a work-based problem or one that is driven by your own findings.
Individual Research Project (30 credits)
The 30-credit Individual Research Project (IRP) builds on your Research Project Proposal, defining and developing a plan for research within a particular field of your choice. The IRP is the implementation and write-up of these results. A self-study module, you’ll draw on skills acquired throughout the degree, including self-management, deadlines and subject knowledge.