MSc Advanced Computer Science with Business
Please note: This page is for 2027 entry. Click here for 2026 entry.
| UCAS code | 1234 |
|---|---|
| Duration | 1 year full time 2 years part time |
| Entry year | 2026 |
| Campus | Streatham Campus |
| Typical offer | 2:1 Honours degree |
|---|---|
Why study MSc Advanced Computer Science with Business at Exeter?
- This programme is an ideal course for you if you have graduated from a computer science background* and wish to build on your existing knowledge of computer science whilst learning key business and management skills.
- This flexible programme is taught in partnership with the Business School and gives you the opportunity to choose a mix of Computer Science and Business modules that suits your interests.
- You can combine fundamental Computer Science modules with modules in Management, Strategy, Marketing and Accounting to prepare you for working with data in a leadership or management role.
- Learn from teaching that draws directly from our particular research strengths in AI, machine learning, data science, high-performance computing and networks, and cyber-security.
- Explore the latest techniques and technologies, and how to apply these to complex contemporary problems across the breadth of society.
- Our latest facilities for computer science students are world-class spacious teaching labs allowing comfortable, collaborative working in a sensory-friendly environment fully supported by your teachers.
- Your project, which forms a major part of your masters, will be business-focussed as you explore data science in a commercial environment, preparing you for your next steps.
*If you are interested in an MSc in computer science but do not meet the entry requirements for this programme, you are welcome to apply for MSc Computer Science or MSc Data Science.
Fast Track (current Exeter students)
Discover MSc Advanced Computer Science with Business at the University of Exeter.
Top 10 in the UK for graduate prospects
Joint 9th for graduate prospects for Computer Science in the Complete University Guide 2027
Long-established partnership with the Alan Turing Institute and home to the Institute of Data Science and Artificial Intelligence
Excellent facilities spanning a wide range of machine types and software ecosystems alongside world-class computer science labs
Courses designed to launch and develop careers for those working in or entering data and technology-driven roles
Entry requirements
Applicants are required to have at least a 2:1 degree in computer science or a related area. This is an advanced programme and requires substantial previous knowledge of computer science (equivalent to that gained from an undergraduate degree in this area).
Applicants must be able to show evidence of good programming ability in a recognised modern computer language. Applicants may be interviewed by video conference to assess their programming ability and suitability for the course.
We may consider applications with non-standard qualifications where there is evidence of exceptional performance in modules relevant to the programme of study, significant relevant work experience, or relevant professional qualifications. If you do not meet the entry criteria for this programme, please consider our MSc Computer Science or MSc Data Science programmes which are open to students from non-computing backgrounds.
Please also see our guidance on essential documentation required for an initial decision on taught programme applications.
Entry requirements for international students
Please visit our entry requirements section for equivalencies from your country and further information on English language requirements.
Please also see our guidance on essential documentation required for an initial decision on taught programme applications.
Entry requirements for international students
English language requirements
International students need to show they have the required level of English language to study this course.
The required IELTS test scores for this course fall under Profile B1.
Please visit our English language requirements page to view the required test scores and equivalencies from your country.
Course content
Computer Science is a wonderful, complex and curiosity-driven scientific field in its own right, but it enables, facilitates and supports so many other fields of scientific inquiry and is applied to so many real-world problems that it affords you the opportunity to take your research or career almost anywhere.
Our Advanced Computer Science with Business MSc course design offers you the flexibility to choose the modules that match your areas of interest. Our computer science modules cover fundamental skills such as high performance computing, machine learning, modelling and simulation, social networks and text analysis, and security. You can choose from a selection of business modules covering accounting, competitive strategy, leadership, operations, innovation, digital transformation and marketing.
Your final project brings together computer science and business as you explore data science in a commercial environment. Our academics have connections with industrial partners such as the National Trust, Met Office and the NHS which means there are opportunities for your research project to be linked to a real-world problem. Whatever you choose to research, the size and diversity of our department means that you will be able to choose an academic supervisor closely aligned with your research goals. We offer you dual supervision - your primary supervisor is likely to be from the Business School and a computer science colleague will act as a secondary supervisor to support with the computer science elements of your project.
Part time students will complete 60 credits in your first year and another 60 credits plus your project (ECMM454 Computer Science Business Project) in your second year.
Full time students will study 60 credits plus beginning your project module in term one, a further 60 credits in term two and term three will be used to complete your project.
The modules below provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.
Please note that the module information displayed here is subject to change.
60 credits of compulsory modules, 120 credits of optional modules
You may select up to 75-90 credits from Optional Group 1.
You may select up to 15 credits from Optional Group 2.
You must select at least 30 credits from Optional Group 3.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| Compulsory 1 | ||
| Research Project | 60 | |
COMM514: Research Project
In this module, you will work on a research problem in an area relating to your programme of study, applying the tools and techniques that you have learned throughout the modules of the programme. This is an independent project, supervised by an expert from the relevant area, and culminates in writing a dissertation in the form of a research paper, describing your research and its results.
Research topics can be selected from across the breadth of computer science, data science and related topics. The project may include theoretical analysis, as well as practical software implementation.
This module aims to give you in-depth experience of research in an area relating to your programme of study. It will help you prepare for projects both in an industry or commercial setting, as well as in further postgraduate research work, such as a PhD. The module builds on the knowledge and skills you have acquired in the taught modules of the programme to allow you to investigate an area of particular interest to you. It aims to give you experience of many aspects of research work, including problem formulation, literature review, planning, tool development, experimentation, analysis and presentation of results.
Optional modules
| Code | Module | Credits |
|---|---|---|
| Optional 2 | ||
| Methods for Stochastics and Finance | 15 | |
| Analysis and Computation for Finance | 15 | |
| Fractal Geometry | 15 | |
| Mathematical Theory of Option Pricing | 15 | |
| Engaging with Research | 15 | |
| Computational Modelling | 15 | |
| Advanced Topics in Mathematical and Computational Biology | 15 | |
| Representation Theory of Finite Groups | 15 | |
| Metric Number Theory and Diophantine Approximation | 15 | |
| AI and Data Science Methods for Life and Health Sciences | 15 | |
| Advanced Topics in Statistics | 15 | |
| Dynamical Systems and Chaos | 15 | |
| Fluid Dynamics of Atmospheres and Oceans | 15 | |
| Modelling the Weather and Climate | 15 | |
| Algebraic Number Theory | 15 | |
| Algebraic Curves | 15 | |
| Waves, Instabilities and Turbulence | 15 | |
| Magnetic Fields and Fluid Flows | 15 | |
| Statistical Modelling in Space and Time | 15 | |
| Research in Mathematical Sciences | 15 | |
| Space Weather and Plasmas | 15 | |
| Bayesian Statistics, Philosophy and Practice | 15 | |
| Ergodic Theory | 15 | |
| Fundamentals of Weather and Climate Science | 15 | |
| Mid-latitude Weather Systems | 15 | |
| Climate Change Science and Solutions | 15 | |
| Topics in Analytic Number Theory | 15 | |
| Data-driven Analysis and Modelling of Dynamical Systems | 15 | |
| Uncertainty Quantification | 15 | |
| Quantitative Methods and AI for Environmental Challenges | 15 | |
| Introduction to Data Science and Statistical Modelling | 15 | |
| Applications of Data Science and Statistics | 15 | |
| Data Science and Statistical Modelling in Space and Time | 15 | |
| Statistical Data Modelling | 15 | |
| Communicating Data Science | 15 | |
| Bayesian Philosophy and Methods in Data Science | 15 | |
| Optional 1 | ||
| Network Science | 15 | |
| Text Mining and Natural Language Processing | 15 | |
| Deep Learning | 15 | |
| Nature-Inspired Computation | 15 | |
| Research Methodology | 15 | |
| Computer Modelling and Simulation | 15 | |
| Computer Vision | 15 | |
| High-Performance Computing | 15 | |
| Fundamentals of Security | 15 | |
| Data Governance and Ethics | 15 | |
| Optional 3 | ||
| Accounting for International Managers | 15 | |
| Managing Competitive Strategy | 15 | |
| Leadership and Global Challenges | 15 | |
| Managing Operations | 15 | |
| Marketing Strategy | 15 | |
| Digital Transformation | 15 | |
COMM039: Network Science
Many of the most important datasets are relational: friends and followers on social media, users who buy similar products, towns connected by roads, computers connected by routers and so on. Network Science is how we study and understand large relational data sets. In this module you will study how to represent, visualise, summarize and analyse large networks to learn about communities, epidemics, transport and resilience in real systems. This module is appropriate for students interested in data science and requires some programming and math background.
This module aims to give students the expertise to model and analyse large network datasets. After a grounding in the basics of network science we move on to more advanced techniques and algorithms to perform rigorous analysis of large networks and showing how these methods can be applied to real data sets.
COMM040: Text Mining and Natural Language Processing
Text mining is the process of extracting insight from large collections of written documents. Recently, there has been immense progress in how computers understand human language. This means reviews, tweets, archives of legal documents, recipes and all kinds of text can now be effectively analysed. This module teaches you how to search, group, summarise and understand large corpuses of documents. The course will cover methods like topic modelling, sentiment analysis, translation and the use of Large Language Models to solve real world problems. The student should have taken or be taking a module on the basics of machine learning.
Students will understand and apply modern NLP methods to real world textual datasets. The focus will be on methods for generating insight from large collections of text, from practical first steps, like data cleaning and validation, to topic modelling using a variety of cutting-edge techniques.
COMM113: Deep Learning
Deep Learning is a highly in-demand skill in AI. In this module, you will study foundational and advanced deep learning techniques, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn key concepts, including, for example, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and contemporary advancements such as Transformers, with practical applications across various domains. You will attend lectures providing in-depth coverage of theories and algorithms. In addition, you will attend lab sessions where you'll apply theoretical concepts to hands-on practices. This module is suitable for Computer Science, Mathematics and Engineering students and any students with experience in programming and foundational machine learning concepts.
ECMM409: Nature-Inspired Computation
Traditional computation finds it either difficult or impossible to perform a wide range of tasks including product design, decision making, logistics and scheduling, pattern recognition and problem solving. However, nature is proven to be highly adept at solving problems making it possible to take inspiration from these methods and to create computing techniques based on natural systems. This module will provide you with the knowledge to create and apply techniques based on evolution, the intelligence of swarms of insects and flocks of animals, and the way the human brain is thought to process information. This module is appropriate for you if you have an interest in optimisation and data analysis, and have some programming and mathematical experience.
Non-requisites (cannot be taken with): ECM3412 Nature-Inspired Computation
This module aims to provide you with the necessary expertise to create, experiment with and analyse modern nature-inspired algorithms and techniques as applied to problems in industry and industrially-motivated research fields such as operations research.
The module also aims to provide you with knowledge of the limitations and advantages of each algorithm and the expertise to determine which algorithm to select for a given problem.
MEng AHEP3 ILOs covered on this module:
SM1m-SM6m, EA1m-EA6m, D1m, D3m-D8m, ET3m, EP1m, EP3m, EP4m, EP8m-EP11m, G1m-G4m
ECMM410: Research Methodology
On this module, you will get an introduction to the methods used in scientific research, including finding research articles, critical review, peer review, presentation skills and literature synthesis. In the lectures, there is a strong emphasis on student engagement, and you should be prepared to stand up in front of the class and discuss things you have read.
The aim of the module is to introduce you to some of the soft skills you need to carry out research, such as communication, literature review and critical thinking. Because of the mix of different subjects, it is not possible to cover hard skills such as statistical analysis, because individual students will have a different baseline and have varying requirements for their work.
ECMM424: Computer Modelling and Simulation
This module is designed to equip you with foundational knowledge and useful skills in computer modelling and simulation. Numerous architectures, protocols and algorithms have been proposed for contemporary computer and communication systems. Analytical modelling and simulation play an increasingly important role in computer science and modern engineering, particularly in the design, performance prediction, evaluation, and optimisation of computer and communication systems. In this module, you will acquire useful knowledge of developing cost-effective analytical performance models and gain important skills in design and implementation of computer simulators. A range of case studies are examined, both in the lectures and workshops (laboratory exercises).
PRE-REQUISITE MODULES ECM1410, ECM2414
ECMM426: Computer Vision
How do we recognise objects and people? How can we catch a ball or navigate a busy room without collisions? These everyday tasks have challenged AI scientists for decades. Recent advances in computer vision have led to major improvements in applications such as face detection, body tracking, autonomous vehicles, and action recognition.
This module introduces the fundamentals of computer vision, covering both classical and state-of-the-art methods. You will gain a theoretical understanding of key algorithms, along with practical skills in image processing, feature extraction, object detection, segmentation, and deep learning for vision tasks. The course also explores 3D vision and modern topics such as video analysis and low-shot learning, providing a broad foundation for solving real-world vision problems.
ECMM461: High-Performance Computing
The demand for ever-increasing computational power drives the development and exploitation of high-performance computing that underpins leading edge research in computationally intensive engineering technologies fields. This module is designed to equip you with a solid foundation and useful skills in high-performance and distributed computing. In this module, you will learn about current high-performance computer architectures and how the computer architecture influences the performance of algorithms and programs. You will also develop skills in parallel algorithm design and parallel programming, and will gain experience of using a high-performance computing system.
This module aims to provide you with a thorough grounding in parallel programming and the architectures used in high-performance computing. After presenting the fundamental ideas and basic concepts of high-performance computing, the module outlines the architectures, components and parallel programming of high-performance computers. The module will introduce you to recent developments and future trends in architecture and algorithms in high-performance computing.
ECMM462: Fundamentals of Security
Our modern life depends on the security of computerised systems ranging from social aspects (e.g. phishing) to technical and mathematical aspects (e.g. access control, encryption). In this module, you will learn the fundamental concepts required for starting a career in various areas related to security (e.g. cyber security, data security, information security, computer security). You will learn core security concepts (e.g. authenticity, confidentiality, anonymity, privacy) and core technologies (e.g. encryption, authentication, authorisation). Moreover, you will learn the basic attacks on security systems and approaches for reasoning about the correctness of security techniques.
The aim of this module to create awareness of the need for security and privacy in modern life, and to introduce the fundamental security and privacy mechanism used in modern computer systems. We will explore topics such as fundamentals of computer security, technology and principles of network security, cryptography, authentication and digital signatures, access control mechanisms, privacy, and anonymisation.
In more detail, the aims of the module are to give you an understanding of:
SOCM033: Data Governance and Ethics
Data science, machine learning, artificial intelligence and 'big data' have become central to every aspect of social life. How can these complex and powerful technologies best be managed and governed for the benefit of society now and in the future? In this module you will: (1) identify some of the main risks and ethical/legal challenges involved in the widespread automation and digitalisation of services characterising 21st century life (for example, the clash between individual desire for privacy, frameworks for data ownership and the institutional commodification of personal data); (2) examine whether and how such concerns can be handled; and (3) discuss the responsibilities of data scientists and other producers of technologies for data analysis towards their proper use.
BEAM045: Accounting for International Managers
Summary:
Managers are constantly making decisions which have financial consequences:
- How much to charge for X?
- How much does Y cost to make?
- How much profit could be made if...?
- Should there be investment in this new venture, product, or market?
Questions are always being asked by a wide range of stakeholders:
- How successful is the business?
- Should I invest in it?
- Work for it?
- Buy from it?
- Sell to it?
- Lend to it?
Management and financial accounting information support internal and external business decision-making by all those with an interest and influence.
BEAM045 recognises that good managers need to be able to appreciate and use a variety of accounting information and techniques with professional scepticism in business decision-making.
This module also introduces and encourages skills in providing and professionally communicating content that is relevant and understandable to a range of non-financial clients.
Additional Information:
Internationalisation:
- The concepts and techniques explored in this module have global application; Learning is undertaken in an international context, and you are encouraged to share knowledge and experiences from your own and other countries.
Ethics and Corporate Responsibility:
- These are embedded within all topics studied: concepts and techniques are taught to reflect that it is the responsibility of all organisations to make ethical financial decisions and actions, and to provide financial information so that stakeholders can make their own informed decisions.
Employability:
BEMM068: Managing Competitive Strategy
In this module you will explore strategy and strategic management from a range of different perspectives. In the current business climate there are many significant issues which organisations and their leaders must navigate successfully to survive and prosper. You will have the opportunity to discuss these sources of dynamism and disorder and to think about how strategy has changed over time with many competing theories and schools of practice emerging to provide solutions to the wicked problems facing strategists. If you aspire to a senior management role, to run your own enterprise, or to work in consultancy, this module will help to prepare you to think strategically and to be able to appreciate the long-term view necessary to set the direction for and successfully lead an organisation in the 21st century.
The module focuses on case method for a majority of the time - so you will be working on a variety of case studies applying theory to real world organisations, diagnosing their problems and discussing the actual decisions facing senior managers in those companies as they search for the best solutions. The skills you gain from this are highly valued by employers and provide a good preparation for some styles of interviews and assessment centres used to recruit graduates.
This module is AI integrated, which means there is an expectation that you will use AI during classes and as part of the assessment process
The aims of this module are to
BEMM071: Leadership and Global Challenges
The aim of this module is to provide you with an opportunity to actively and critically engage in debates about the role of leadership in major global challenges facing the world today. In doing so, the module looks to challenge your implicit conceptions of leadership and to develop a more sophisticated understanding of real-world leadership and its challenges. Each topic will be explored in depth through engagement with academic literature theory and research, as well as practical case-study perspectives and real-world examples. Particular attention will be given to how each topic plays out at the interaction of leaders, organisations, and society.
- Destructive leadership
- Inclusive leadership
- Responsible leadership
This module equips you with the ability to apply critical thinking and understand how different types of leadership contribute to the problems and solutions to the world's greatest challenges. This ability to ask critical questions is an essential higher order thinking skill that will underpin all future management practice.
BEMM114: Managing Operations
Summary:
The aim of the module is to introduce you to the importance of the operations functions of an organisation and how operations performance can impact on the success of the whole organisation. The module discusses the role played by operations managers in setting an operations strategy through which products and services can be designed and delivered. The module focusses not only on systems, processes and facilities in the production and flow of goods and services, but also on the general principles an organisation can use to guide its decision-making. Particular attention is given to operational objectives, capacity management, project management and the process choice decisions facing organisations in pursuit of 'delighting' the ever demanding customer; the customer who today typically expects; quality, value for money, and consistently excellent customer service.
BEMM148: Marketing Strategy
The aim of this module is to introduce marketing as a central feature of the strategic planning process. The American Marketing Association defines marketing as the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large. A marketing perspective focuses on an in-depth and critical understanding of desires and decision processes of customers and businesses. This module will introduce the stages of an organisation's marketing strategy as: strategic analysis; strategic choice; strategic implementation; and monitoring and control. Understanding the processes involved in these stages, from both theoretical and practical perspectives will develop participant's awareness of the changing role of marketing in today's organisations. The module content is structured around practical examples and case studies that aim to help you develop skills of critical analysis and problem-solving.
NB: This module is only available to students who have the module listed on their programme specification
BEMM190: Digital Transformation
This module will introduce you to the fundamentals of digital transformation through study of a range of practical examples. Organisations must position themselves for success in the digital era to be sustainable. For new ventures, it means creating structures and working practices appropriate to the dynamic environment. For established organisations, it means transforming existing structures and ways of working to meet current and future needs while continuing to meet the expectations of existing clients, employees and other stakeholders. Consequently, digital transformation activities are becoming increasingly strategic across public, private and third sectors.
You will also assess the implications for career development within these disruptive environments. This means building the digital skills required for success such as effective workplace communications across hybrid locations, the use of collaborative online tools, and the importance of ethical behaviour and wellbeing.
This module will help you to:
Fees
2026/27 entry
UK fees per year:
£12,900 full-time; £6,450 part-time
International fees per year:
£29,800 full-time; £14,900 part-time
Scholarships
The University of Exeter offers a wide range of scholarships to support your education, with £7 million available for international students applying to study with us in the 2026/27 academic year, including our prestigious Exeter Excellence Scholarships. We also provide awards for sport, music and other achievements, as well as regional and partner scholarships with organisations such as Chevening, The Beacon Trust and the British Council. For more information on scholarships and other financial support, please visit our scholarships and bursaries page.
University of Exeter Alumni Scholarship
We are pleased to offer the University of Exeter Alumni Scholarship, a scholarship for University of Exeter alumni beginning a standalone postgraduate programme in 2026/27 with us a scholarship worth 20% of the cost of your first year tuition fees.
Terms and conditions, including deadlines, apply.
Teaching and research
Teaching
Teaching is mainly delivered by lectures, workshops and online materials. Each module references core and supplementary texts, or material recommended by module deliverers, which provide in depth coverage of the subject and go beyond the lectures.
Internationally recognised research
We believe every student benefits from being taught by experts active in research and practice. All our academic staff are active in internationally-recognised scientific research across a wide range of topics. You will discuss the very latest ideas, research discoveries and new technologies, becoming actively involved in a research project yourself. Read more about our current computer science research and our Business School research. The University is also home to the Institute for Data Science and Artificial Intelligence which provides a hub for data-intensive science and artificial intelligence within the University and the wider region. Our research centre, the Initiative in the Digital Economy at Exeter (INDEX) brings together the worlds of business and computer science.
Academic partners
Our long-established partnership with the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence, means that we have strong connections to the UK AI research community. Currently we host 11 Turing Fellows and one Turing AI Fellow at the University. Turing Fellows are established scholars with proven research excellence in data science, AI, or a related field. Lectures, conferences and seminars organised by Turing and the Turing University Network are usually open to our students to attend either in person or online.
Investment in data science and artificial intelligence
The University has invested £50 million in the development of its Data Science and Artificial Intelligence capabilities. The Accelerating Data Science and Artificial Intelligence (ADA) project has been running since 2023 and has invested in teaching, research and infrastructure which this programme benefits from.
Supportive environment
We aim to provide a supportive environment where students and staff work together in an informal and friendly atmosphere. We operate an open door policy, so it’s easy to consult individual members of staff or to fix appointments with them via email. As a friendly group of staff, you’ll get to know us well during your time here.
Assessments
The assessment strategy for each module is explicitly stated in the full module descriptions given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills. Assessment methods include essays, closed book tests, exercises in problem solving, use of the Web for tool-based analysis and investigation, mini-projects, extended essays on specialised topics, and individual and group presentations.
Facilities
World-class facilities
Our latest computing facilities are world-class spacious teaching labs allowing comfortable, collaborative working in a sensory-friendly environment.
You will have the opportunity to carry out work on the University’s High Performance Computing environment, a £3m investment by the University, designed to serve advanced computing requirements.
Careers
Computer Science is at the forefront of technology and innovation. With connectivity at the heart of society, there is an increasing need for graduates who are able to understand the latest techniques and technology to negotiate problems. Huge opportunities exist for the businesses and individuals who can solve these problems using the latest technology such as artificial intelligence, machine learning, data science, high performing computing and cyber security.
Graduate destinations
Career opportunities are limitless, with graduates being found in a variety of sectors, including software engineering, health communications, education, life sciences, finance and manufacturing. This programme is particularly suited to professionals and graduates looking to develop career options or pursue academia.
Dedicated careers support
You will receive support from our dedicated Career Zone team, who provide excellent career guidance at all stages of career planning. The Career Zone provides one-on-one support and is home to a wealth of business and industry contacts. Additionally, they host useful training events, workshops and lectures which are designed to further support you in developing your enterprise acumen. Please visit the Career Zone for additional information on their services.
