MSc Computer Science with Artificial Intelligence
April 10, 2026 2026-04-10 6:54MSc Computer Science with Artificial Intelligence
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85% of research ‘world-leading’ or ‘internationally important’ (latest REF)
Providing education and opportunity since 1827
Courses developed with industry partners
Option to pay per module
Alumni discount available
Ranked No. 1 in the UK university for Teaching First Generation students
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A launchpad for an exciting career in artificial intelligence
An entirely online master’s for forward-thinking individuals who may not have a background in computer science.
The 100% online MSc Computer Science with Artificial Intelligence provides you with an exciting opportunity to launch a career into a high-tech field that is characterised by its exponential growth and its rapidly increasing importance to modern industry and society. Studying this course, you will experience the application of AI in the real world, from image and speech processing through to web chatbots. The emphasis of the course is not only on the theoretical, but also the practical application of this technology in new and ever-evolving domains. This master’s degree equips you with knowledge and skills to recommend solutions and apply existing AI tools to real-world challenges in areas such as business, health, industry. The course has been designed in close consultation with AI experts and leverages unique tools and platforms to deliver the core skills and capabilities required in this field. You will be equipped for innovative roles in areas such as the creative industries, product design and the games industry.On-demand study, from anywhere
A flexible online course design that can be accessed all over the world.
The online MSc Computer Science with Artificial Intelligence has been developed to facilitate learning in parallel with a busy work and family life. The flexible course design means that you can study in your spare time, on demand, at the times that work for you. This ensures that you can study around your other commitments, rather than having to put them on hold. You can continue to earn while you learn, enabling you to apply your new knowledge and skills to your role as you progress in your studies.
All teaching is delivered online through our cutting-edge learning portal, which means that you don’t ever need to visit campus and can study from home, or indeed from anywhere in the world. With six start dates a year, you’re not restricted to the traditional academic year and can begin your postgraduate study within weeks.
International recognition and industry partners
You will learn from a team of highly skilled computer science experts, many of whom actively participate in cutting-edge research, 85% of which has been recognised as ‘world-leading’ or of ‘international importance’. The teaching excellence of the University was also recognised in the form of a ranked No.1 in the UK for Teaching first generation students. University of Wolverhampton computer science students have worked on innovative projects with industry partners, including apps and software development for the NHS and the West Midlands police.
What you will learn
Studying this online master’s programme, you will develop a critical understanding of the processes, techniques, methodologies and hands on applications of artificial intelligence using contemporary software. It equips you with the key skills needed to apply AI tools and techniques to complex real-world situations. You will also develop the communication, management and organisational skills needed to lead data science projects and to communicate findings to the wider organisation including to non-technical audiences.
Knowledge and skills taught include:
- Data science
- Machine learning
- AI technologies
- Applications of AI
- Intelligent agents
- Data mining
- Informatics
- Project management
Specialist AI expertise and teaching excellence
Studying the online MSc Computer Science with Artificial Intelligence, you will benefit from the deep expertise in AI of a research-active team, many of whom are engaged in leading-edge projects. Our research credentials are reflected by the fact that 85% of the research at The University of Wolverhampton was recognised as ‘world-leading’ or of ‘international importance’ in the latest Research Excellence Framework. Our computer science students have partnered with industry on a number of innovative projects, examples of which include app and software development for the NHS and the West Midlands police.
Entry requirements for home and international students
You should normally have, or be about to complete:
A recognised undergraduate or postgraduate degree (or equivalent qualification) from an accredited college, institution, or university, equivalent to or higher than a UK bachelor’s degree with honours.
Or:
If you do not hold a recognised degree or hold an ordinary degree, you should have at least two years of relevant work experience in a professional, managerial or supervisory role.
You will need to have access to a computer with administration access so that you can install the software to be used on the course
Fees
Total course fees:
£6,960
Per 15-credit module fee:£580
If you are based in the UK, you may be eligible for a government postgraduate loan to cover the full costs of the course. You will need to self-fund your first module/s to enrol. University of Wolverhampton alumni discount: If you have successfully completed an undergraduate degree at the University of Wolverhampton, you are eligible for a 10% tuition fees reduction.
Per 15-credit module fee:£580
If you are based in the UK, you may be eligible for a government postgraduate loan to cover the full costs of the course. You will need to self-fund your first module/s to enrol. University of Wolverhampton alumni discount: If you have successfully completed an undergraduate degree at the University of Wolverhampton, you are eligible for a 10% tuition fees reduction.
Modules
Modules Concepts and Technologies of Artificial Intelligence
Human intelligence involves a continuous process of sensing, analysing, reasoning, and adaptation. In this course, you will focus on studying algorithms (both learning and optimisation), which could be used to develop an artificial intelligence (AI) system. You will focus in particular on theory and implementation using different programming languages. This module will provide you with opportunities to comprehend, define, and formulate real-world problems, integrate learning and optimisation algorithms such as artificial neural networks and genetic algorithms, and select optimal machine learning, training, and reasoning algorithms.
Deep Machine Learning
This module’s main focus is on the fundamentals of machine learning (ML), covering both basic and advanced concepts, including philosophy, linear algebra, big data, optimisation, and information theory. You will study some of the key AI models such as deterministic models, stochastic models, Markov chain, linear regression, logistic regression, gradient descent, softmax regression, principal component analysis (PCA) and eigenvectors, multilayer perceptron (MLP) and backpropagation, amongst others. There is a strong emphasis on tying the underlying theory to applications to real-world situations. After studying this module, you will have a comprehensive understanding of ML algorithms and have in-depth computational knowledge, problem formulation, and be able to code and apply these ML algorithms.
Data Science
This module is designed as an introduction to some of the central concepts and tools used in data science. As such it includes discussions on data capture, maintenance, processing, analysis and communication. You will examine a series of real-world case studies, and state-of-the-art software and algorithms will be used as tools within these case studies. You will explore: an introduction to data science; data capture; acquisition of data; data maintenance; data processing; data analysis; data communication; and intelligent decision making. On completion of this module you will be able to extract meaning from data and communicate that meaning to non-specialist audiences, and you will be able to use software in the application of specialist algorithms and approaches to data processing and analysis.
Data Mining and Informatics
This module looks at different data processing and mining techniques and state-of-the-art data processing and mining tools. The topics you will explore include an introduction to data mining and knowledge discovery process, data collection and processing with data types from a variety of sources, and social web mining. You will look at a variety of techniques and trends in data mining and will develop an understanding of: data models; the knowledge discovery process; data selection; pre-processing and cleaning; data mining algorithms and association rules; classification; clustering; text mining; social media mining; and data visualisation. After studying this module, you will be able to use all aspects of the knowledge discovery process from data collection and data processing to representation, applying cutting-edge data mining techniques to extract information from data. You will also develop your own data mining solution using a state-of-the-art data mining tool.
Applying Artificial Intelligence
This module provides you with hands-on, cutting-edge AI training with application to a wide range of real-world problems, including audio-visual speech processing, image and object recognition, fraud detection, deception detection and anomaly detection. This module will provide you with opportunities to: study concepts such as multimodal and context-aware computing; understand both basic and advanced pre-processing required for different data types (e.g.audio, video, text, EEG); and learn the application of optimisation, big data, and deep learning algorithms using popular AI and machine learning tools. There is a strong emphasis on coupling the underlying theory to an application to real-world situations. After studying this module, you will be able to demonstrate a thorough understanding of efficient context-aware strategies, required to comply with different application requirements and constraints, comprising trade-offs among computational complexity, processing time, and available datasets, and will be capable of solving a wide range of real-world problems using AI tools.
Intelligent Agents
Intelligent agents are programs that can perceive their environment through sensors and can change the state of their environment through actuators. Environments can be fully software-based such as a computer game in which an agent can learn how to play or a physical real-world environment where the agent controls a robot and helps it to navigate around obstacles to reach its destination. You will explore topics including: logic based and reactive architectures; layered architectures; temporal difference learning; TD-Gammon – SARSA; and Q learning – A3C algorithm. After studying this module, you will have a comprehensive understanding of the principles of reinforcement learning and how it can be used in practical scenarios and be able to evaluate alternative architectures for the design and implementation of intelligent agents.
Data Visualisation
Data visualisation is an important visual method for effective communication and analysing large datasets. With the rapid increase of data volume and complexity, users often find it difficult to understand and make sense of the data. Through data visualisation, data is presented in a meaningful and interactive way to users, so that they can draw conclusions that sometimes are not immediately obvious, and hence manipulate and use the data for exploration, learning, communication, problem resolution and decision making. The module will provide you with the knowledge of theoretical concepts of interactive data visualisation and presentation, creative design processes as well as the applications of interactive visualisation and presentation tools and techniques. You will explore: history of data visualisation; planning a visualisation; designing a narrative around data; how to create the right charts for your data; elements of poor design; perception; interactive data visualisations; use of software; and communication and telling a story with data. On completion of this module you will be able to understand and apply the fundamental concepts and techniques in data visualisation and use specialist software such as Tableau to produce visual insights into data and to present your findings to a non-specialist audience.
Project Management
In this module you will learn to use a wide variety of tools, techniques, methodologies and processes in the field of project management. Ethical and legal aspects of project planning and management will also be discussed. You will explore: project management and associated risks; risk handling techniques and methodologies; management of organisational resources and budgeting; legal, social, ethical and regulatory requirements and issues; planning, estimation, structure of projects; monitoring and control, review of scientific processes; and employability issues. You will develop a comprehensive understanding of the concepts of project management and its crucial operation in complex and unpredictable environments. By studying this module, you will develop a critical understanding of methodologies underpinning core project management processes and procedures to assure project success and minimise risk, and be able to flexibly and autonomously apply knowledge of solutions and processes that underpin professional practice in project management.
Virtualisation and Cloud Computing
This module explores the concepts and practice of virtualisation and cloud computing. You will examine the virtualisation and cloud computing solutions commonly used in industry and you will develop an understanding of the key aspects and principles of their operation. After studying this module, you will be able to demonstrate a critical understanding of the concepts, issues and considerations of virtualisation and cloud computing, and demonstrate mastery of the tools and advanced techniques used in the development of sophisticated solutions.
Research Methods and Statistics
This module introduces you to research and methodologies used to underpin scientific work, data analysis, hypothesis establishment and artefact validation in understanding research of an appropriate subject discipline. The module explores: an introduction to research; literature search, discussion and critical evaluation; research methodologies and strategies; experimental procedures; data analysis methods; research philosophy; identification of a suitable project title; research impact and gap analysis; production of scientific work; consistency, rigour and clarity; ethics in research; and legal, social and regulatory requirements and issues. You will be actively engaged in enquiry during the learning process and have to articulate your own understanding of the issues examined during teaching sessions. You will understand the concepts of research and its crucial operation in complex and unpredictable environments where a range of techniques and technologies coexist to identify gaps in the existing literature. You will develop your collaborative abilities through the learning process as part of the task to cross-fertilise and discuss research ideas about the technologies analysed and their core implementation challenges and benefits with fellow students. You will be given the opportunity to select and examine specific research problems and to reflect and exercise research methods, title decomposition and research question formulations. By studying this module, you will develop a critical evaluation and understanding of knowledge on various research principles and methodologies and be able to flexibly and autonomously apply knowledge of solutions to open research problems, demonstrating the ability to understand research impact and develop gap analysis tools and techniques.
Dissertation
One of the most important skills expected of being an effective specialist in any discipline is the ability to work creatively under the appropriate guidance of an organisation. It is therefore essential that you use and develop the skills and knowledge gained from other modules and from your wider educational or working background in a major integrative exercise. In this module, you will be expected to develop an idea and demonstrate your ability to develop it further by applying your technical, analytical, practical and managerial skills in an integrated manner. This module will support you to autonomously develop your research skills and problem-solving skills to build a novel artefact that encompasses the theoretical domains and hands-on analysis and ideation during your course. You will engage in an informative tutorial on how to apply your knowledge from research methods in the design of your artefact and research questions. This module will enable you to demonstrate a deep and systematic understanding of a selected specialist area of your course, including issues at the forefront of research or professional practice in your chosen area. You will be able to independently design and undertake a substantial investigation that rigorously tackles a complex problem in computer science, selecting appropriate methodological processes and critically evaluating their effectiveness.