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Top 20 in the UK for Computer Science
Top 10 in the UK for graduate prospects
Joint 9th for graduate prospects for Computer Science in the Complete University Guide 2027
94% of our Computer Science research outputs are internationally excellent
Based on research outputs rated 4* + 3* in REF 2021, submitted to UoA 11 Computer Science and Informatics
Course content
The MSc Computer Science (Online) degree is designed for students who want to develop advanced computing knowledge and skills through flexible, part-time study. Delivered fully online, the programme provides a structured route into key areas of modern computer science, including artificial intelligence, machine learning, data science and cyber security.
You'll begin by building foundations in programming, mathematics and computational thinking before progressing to specialist topics and applied project work.
Drawing on the University of Exeter's research strengths and designed to support students from a range of academic and professional backgrounds, the programme combines academic rigour with practical learning that prepares you for careers across the digital sector or further study.
Modules
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.
180 credits of compulsory modules. The modules are offered on a carousel model where you may join the programme at one of three points each year.
Compulsory modules
| Code | Module | Credits |
|---|---|---|
| Compulsory 1 | ||
| Foundations of Computer Science | 30 | |
| Algorithms and Data | 30 | |
| Introduction to Data Science | 30 | |
| Machine Learning | 30 | |
| Computer Vision | 30 | |
| Cyber Security | 30 | |
COMM045Z: Foundations of Computer Science
Foundations of Computer Science is the first module undertaken by all students on the programme. It establishes the programming and quantitative foundations required for subsequent postgraduate study in Computer Science.
The programming strand introduces software development using Python. You will learn how to decompose computational problems, represent and manipulate data, control program flow, develop reusable functions and classes, handle errors, work with files, and apply appropriate testing and debugging practices. You will also consider the responsible use of generative AI within software development.
The quantitative strand develops the mathematical and statistical reasoning needed to understand and solve computing problems. It covers probability and statistics, algebra and linear algebra, calculus, modular arithmetic, binary representation and numerical optimisation. These topics are introduced with an emphasis on their relevance to computation and subsequent study in areas such as algorithms, data science, machine learning and cybersecurity.
Together, the two strands develop the computational problem-solving, programming and mathematical reasoning skills needed to progress through the MSc Computer Science programme.
COMM046Z: Algorithms and Data
This module introduces the foundations of efficient computing: how problems are solved and how information is organised. You will learn to design, express and compare algorithms using Big O notation, then apply these ideas through key data structures such as arrays, lists, stacks, queues and trees. You will also study sorting, searching, recursion and divide-and-conquer techniques.
The module then moves from program-level data handling to database-level data management. You will explore how data is modelled, stored and queried through database systems, ER modelling, the relational model, SQL, physical database design and normalisation.
Through coding tasks, worked real-world examples, visualisations and database exercises, you will build practical skills for selecting suitable algorithms, data structures and data models for real computing problems. The module provides a foundation for software development, data science, artificial intelligence and systems design.
COMM047Z: Introduction to Data Science
This module combines an introduction to the principles and practice of data science with an individual applied research project. You will develop core data science skills including data acquisition and wrangling, exploratory analysis and visualisation, statistical modelling, network analysis and text analysis, while considering the responsible use of data in business and society.
The taught component provides the concepts, methods and practical experience needed to formulate and investigate data-driven problems. You will then apply and integrate this learning through an individual research project, supported by academic supervision. The project will require you to define an appropriate problem, select and justify suitable methods, analyse and evaluate results, and communicate your findings through practical work, a concise research report and live academic conversation.
The module therefore develops both technical competence in data science and the ability to conduct and communicate an independent investigation.
COMM422Z: Machine Learning
This module combines advanced study of machine learning with an individual applied research project. You will develop a theoretical and practical understanding of statistical machine learning, pattern recognition, classification, probabilistic modelling, neural networks, generative methods and reinforcement learning, together with appropriate approaches to model evaluation and responsible machine learning.
The taught component provides the concepts, methods and practical experience required to formulate and investigate machine learning problems. You will apply and integrate this learning through an individual project, supported by academic supervision, in which you will define a problem, select and justify appropriate methods, develop and evaluate a computational solution and communicate your findings through practical work, a concise research report and live academic conversation.
In this data-driven era, modern technologies are generating massive and high-dimensional datasets. This module aims to give you an understanding of computational methods used in modern data analysis.
COMM426Z: Computer Vision
Computer vision enables computers to interpret and reason about visual information from images and video. In this module, you will explore how computational systems can recognise objects and people, analyse movement, understand scenes and extract meaningful information from visual data. You will develop both theoretical understanding and practical skills in core areas of computer vision, including image processing, feature extraction and matching, object detection and recognition, image segmentation, tracking, 3D vision and deep learning approaches. Practical activities will demonstrate how these techniques are applied in areas such as autonomous systems, healthcare, surveillance, robotics and image analysis.
You will apply and extend this learning through an individual research project in an area relevant to computer vision or your wider programme of study. Supported by academic supervision, you will define an appropriate problem, select and justify suitable methods, implement and evaluate a solution, critically consider its capabilities and limitations, and communicate your findings through practical outputs, a concise research report and live academic conversation.
COMM462Z: Cyber 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. 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.
Entry requirements
A 2:2 Honours degree, or international equivalent, in any subject.
We also welcome applications from candidates with relevant professional experience or professional qualifications.
Entry requirements for international students
International students need to show they have the required level of English language to study this course.
The required test scores for this course fall under Profile B1.
Pay as you study
Fees:
£10,000 in total
The fee shows the total amount it will cost if you complete the degree if you take the minimum time of two years. If you take longer than two years, for example, because you take one or more breaks between modules, the total fee you pay may increase slightly due to inflation.
Pay as you study
To make it easier to budget, you don’t need to pay the total fee upfront. Instead, you can pay for each module as you are about to start studying it. You can pay for the whole year if you prefer, but the minimum payment is at least the cost of the module(s) you are taking that term. Please note that if your payment has not reached us by the end of week one of a module, you will have to wait until the next term to start.
Find out more about the funding opportunities available to you, including the UK government postgraduate loan scheme.
How to pay
You can pay online using a credit or debit card. We are unable to give you access to your study materials before your payment reaches us so it’s important to have your finances in place and pay when prompted to ensure you can access your studies at the start of each term.
Other costs to consider
As well as your fees, there are some potential additional costs to be aware of to ensure that you give yourself the best chance of success. These include a suitable computer or device to study and work from, an adequate internet connection to access your learning materials and connect with others, and a comfortable place to study.
Solomon is an Associate Professor of Computer Science at the University of Exeter. He is a leading expert in pervasive and mobile computing, computer science education, and human-centered AI. He holds a Senior Fellowship from the Higher Education Academy (SFHEA).
Before joining the University of Exeter, Solomon was an Associate Professor in Pervasive and Mobile Computing at Luleå University of Technology in Sweden. He also worked as a postdoctoral researcher in the School of Computing at the University of Eastern Finland, where he served as a principal investigator on a large-scale EU, Latin American, and Caribbean project. This project focused on developing a smart ecosystem for learning and inclusion.
Programme Director
Professor Solomon Oyelere" />
Teaching and learning
How you'll learn
This MSc Computer Science (Online) is delivered fully online and designed to fit around professional and personal commitments. You'll follow a structured learning pathway that develops your knowledge progressively, from foundational concepts through to advanced areas of computing.
Studying part-time over 24 months, you'll be able to start in January, May or September through the programme's carousel delivery model.
Contact hours
You should expect to spend around 10-12 hours per week on your studies. This includes engaging with learning materials, participating in online activities, independent study and completing coursework and project work.
Tutorial support
You'll study alongside learners from a range of academic, professional and geographical backgrounds. Regular interaction with academic staff and fellow students provides opportunities to discuss ideas, share perspectives and deepen your understanding of key topics.
Assessment
Assessment focuses on applying your knowledge to practical problems. Through coursework and project-based assignments, you'll demonstrate your understanding of key concepts while developing technical, analytical and problem-solving skills.
Meet the MSc Computer Science (Online) academics
You'll learn from academics in Exeter's Department of Computer Science, whose teaching draws on expertise across artificial intelligence, machine learning, data science and cyber security. You'll benefit from a research-informed curriculum that connects emerging developments with practical applications.
Our current research is organised into four key themes: Secure and Distributed Systems; Machine Learning and Optimisation; Computation, Environment and Society; and AI for Humans and Health.
The MSc Computer Science (Online) is taught by a team of leading academics and practitioners, including:
What opportunities does an online MSc in Computer Science lead to?
Employer-valued skills
You'll develop technical and transferable skills that are valued across the digital sector, including programming, data analysis, computational thinking, problem-solving, analytical reasoning and digital literacy. Through practical and project-based learning, you'll build the ability to apply computing knowledge to real-world challenges.
Career paths
Graduates may pursue opportunities across technology, data and analytics, artificial intelligence, machine learning, cyber security, and IT consulting.
Typical roles include:
- Software Engineer
- Data Analyst
- Data Scientist
- Machine Learning Engineer
- Cyber Security Analyst
- Systems Analyst
- Cloud Engineer
- DevOps Engineer
- Technology Consultant.
Opportunities across sectors
The skills developed on this programme are relevant to a wide range of industries. Graduates may work in technology companies, financial services, healthcare, government organisations and the wider digital and creative sectors.
Career support
As an Exeter student, you'll have access to our career and employability support, helping you explore career options, develop professional skills and prepare for your next steps after graduation.
Further study
The programme also provides a strong foundation for further academic study. Graduates may choose to progress to doctoral research in computer science and related disciplines.
Study a 100% online Masters degree in Computer Science at a Top 20 University*
Apply now for January 2027 entry »
Apply now for May 2027 entry »
* 16th in The Times and Sunday Times Good University Guide, 16th in The Guardian University Guide 2027 and 11th in the Complete University Guide 2027
