MSc Computer Science with Data Science
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Graduate in 14 months full-time, or 24 months part-time.
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Ranked 12th for employment outcomes in the UK*
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Total fees: £7,680 – pay in full or pay per module.
Graduate in 14 months full-time, or 24 months part-time.
Ranked 12th for employment outcomes in the UK*
Total fees: £7,680 – pay in full or pay per module.
Graduate in just 14 months.
Start within weeks with monthly start dates.
Competitive tuition – £7,680 total.
89% of Walbrook graduates in skilled roles*
Curriculum driven by emerging technologies.
Career support and events, 24/7 job portal.
Study flexibly within a weekly structure.
Flex between full and part-time.
Built for digital from day one.
Shape the future of a data-driven world as a data scientist, data analyst, or business intelligence professional.
With Big Data and AI ranked among the fastest-growing skills globally, this MSc in Computer Science with Data Science accelerates your progression into this high-growth sector. You’ll develop a comprehensive understanding of how big data is captured and structured – and how to turn it into insights that deliver value. You’ll work with cloud computing tools, machine learning algorithms, data analytics techniques, and data visualisation tools, while strengthening your problem-solving skills and leadership abilities. You'll complete a final research project to investigate your own area of interest, from big data analytics and data mining algorithms to the knowledge discovery process.
Designed in London – one of Europe’s key data and tech hubs – the programme reflects current trends in analytics, business intelligence and AI adoption across industries. You'll study 100% online, guided by expert lecturers and supported by a dedicated Student Success Coordinator, while you gain essential computing expertise alongside advanced data science skills.
Apply now for a Master’s in Computer Science with Data Science programme that prepares you to thrive in the data-driven economy.
100% Online, distance learning
Start dates:
Start any month
Duration:
Full-time: 14 months
Part-time: 24 months
Tuition fees and funding:
Total programme cost is £7,680
Secure your place by paying for your first one or two modules, depending on whether you choose full-time or part-time study.
Entry requirements:
2:2 honours degree and above (or equivalent) in a subject other than computing.
Alternatively, you can apply with a non-honours degree and 2 years’ professional experience in one or more computing-related roles.
The prices shown below are for our online MSc Computer Science degrees only. They are inclusive of your first module(s) payment and don't include any reductions.
Full-time: 14 months | Part-time: 24 months
£7,680
in total
You'll study 10x 15-credit modules and 1x 30-credit Research Project module in total (approx. 17-30 hrs/week).
Full-time: 14 months | Part-time: 24 months
£640
per 15-credit module
You'll study 10x 15-credit modules. Your final 30-credit Research Project module will be charged at £1,280.
Total tuition fees: £7,680. You can pay for your MSc Computer Science with Data Science degree per module, or in full before you start your studies.
If you choose to pay in full, you’ll receive a 15% reduction on your total tuition fees.
If you choose to pay per module, your payment schedule will depend on whether you choose full or part-time study:
If you apply as a full-time student, you’ll need to pay for two modules upfront to confirm your place, then continue to pay in two-module instalments as you progress.
If you apply as a part-time student, you’ll pay for one module upfront, then continue to pay per module before each one begins.
If you’re a UK student, you may be eligible for a government master's loan from Student Finance England for our online master's degrees. The Student Loans Company (SLC) will pay the loan directly to you after you start your studies. So, it’s your responsibility to make your module payments to us directly. Find out more about funding your Walbrook master's with a UK master's loan >
Want to see exactly when payments are due? Open the payment schedule for our next two start dates below.
April 2026 start date
May 2026 start date
Alumni receive a 10% tuition fee discount. If you’re eligible, our enrolment team can provide your personalised payment schedule.
Every application is different. If you’re not sure whether you meet the MSc Computer Science with Data Science entry requirements, or you have any questions, contact us for advice.
To apply, you’ll need to meet the following entry requirements:
A UK honours degree at 2:2 or above (or equivalent international qualification) in a subject other than computing.
If you hold a non-honours degree and 2 years’ professional experience in one or more computing-related roles, you’re still encouraged to apply. We’ll review your academic and professional background on a case-by-case basis. Applicants without a first degree but with more than two years’ relevant professional experience in computing-related roles may be considered.
Thinking of transferring institutions or have you studied before? You can apply to transfer up to 60 credits towards your master's degree. Please note that credits can’t be awarded for the research module of this programme.
These credits must be relevant, current, and aligned with the subject matter of your chosen MSc Computer Science pathway.
Review our recognition of prior learning process.
Speak to our Enrolment Team.
Submit a recognition of prior learning form alongside your application.
Overseas qualifications may be accepted and will be subject to evidence of equivalency normally verified through ECCTIS (UK ENIC).
If English isn't your first language, you’ll be asked to provide proof of your English language proficiency in one of the following forms. Alternatively, you may be accepted if you have previously studied in English at an appropriate level and attended a recognised institution.
IELTS
Evidence of a score of IELTS Level 6.0 or above with no element below 5.5.
TOEFL iBT®
Evidence of a score of 79 overall (with 18 in reading, 17 in listening, 20 in speaking and 21 in writing).
Trinity College London Integrated Skills in English (ISE)
Evidence of a score of ISE II with distinction in each skill.
Cambridge Certificate of Proficiency or Cambridge Certificate of Advanced English
Evidence of a score of 170 overall, with 160 in each component.
I am currently in full time employment, so being able to study at my own time and being able to be in control of my own studying was really important, and Walbrook provided that as part of their online degrees. Their model really works because you're able to juggle it around your current lifestyle more than the typical degree. Whether you're studying, whether you're part time, or whether you're parents, I would say just go for it.
This 100% online MSc Computer Science with Data Science gives you the practical skills to work confidently with complex datasets, build intelligent systems, and deliver insights that drive change.
You’ll develop a deep understanding of computing principles and data science techniques, learning through theoretical knowledge and practice with programming languages, data analysis, data visualisation, and machine learning algorithms. The programme ends with an independent research project shaped by your interests – whether in big data analytics, data mining algorithms, or the knowledge discovery process.
On this online MSc Computer Science with Data Science programme, you’ll study a series of carefully designed modules. With flexible monthly starts, you’ll join the next available module and study alongside a cohort of computer science master's students learning the same subject at the same time.
Business Data Analytics
Learn how to interpret and present complex datasets to support better decision-making. Explore data analytics techniques, data visualisation, and predictive modelling, and understand how to align analytical approaches with business goals.
Machine Learning: Principles and Programming
Dive into the algorithms that power predictive models. You’ll programme, train, and test machine learning systems using the industry standard Python programming language, applying them to real datasets to solve problems in areas like forecasting, classification, and pattern detection.
Software Engineering
Master the principles and practices that make complex software systems reliable, maintainable, and scalable. You’ll use established development approaches, learn how to handle complexity, and see how new trends are influencing the way software is built.
Modern Database Systems
Develop the skills to design, implement, and manage databases for large-scale data projects, using industry standard Tools such as MariaDB and MongoDB. Learn to design and manage relational and NoSQL databases, optimise performance, and make smart storage choices that boost the scalability, speed, and security of data models.
Fundamentals of Artificial Intelligence (AI)
Understand the core ideas behind AI and machine learning – and how they’re strategically applied to common business problems. You’ll experiment with tools to solve realistic problems, interpret results, and weigh up the commercial and ethical impact of using AI.
Information Systems Development
Analyse requirements and create systems that manage and process data effectively, using HTML, CSS and JavaScript programming languages. Blend theory with design practice to build secure, user-focused solutions that work in challenging organisational environments.
Computer Networks
Explore how data moves between systems and how to keep it secure in transit. Study network architecture, protocols, and performance optimisation, and gain the practical skills to configure and monitor networks.
Cloud Computing
Understand how to use cloud computing platforms for storing, processing, and analysing data. Explore virtualisation, networking, and containerisation, and address the benefits, challenges, and security needs of cloud environments.
Project Management and the Computing Professional
Develop the leadership and project management skills to guide data-driven projects to successful completion. Learn about systems modelling, risk management, resource planning, and effective communication.
Research Development
Prepare for your final project by refining your research question, exploring research methodologies, and evaluating relevant literature. Address the ethical and professional considerations of your chosen topic.
Research Project
Investigate a data science topic that matters to you – from big data analytics to data mining or knowledge discovery. Demonstrate use of research methods, original thinking, critical understanding, and the ability to create data-driven solutions to answer your research questions.
Your module schedule depends on the month you start, and whether you study full or part-time. You'll study each module once, completing all taught modules before moving on to your final two modules: Research Development and Research Project.
|
Module start date |
Module name |
Assessment details |
| 6 April 2026 | Cloud Computing |
1. Graded discussion board – 10% 2. Assignment 1 – 30% 3. Assignment 2 – 60% |
| 4 May 2026 | Information Systems Development |
1. Individual written assignment – 20% 2. Design diagrams and narrative – 20% 3. Technical report with implementation evidence – 60% |
| 1 June 2026 | Software Engineering |
1. Graded discussion board – 10% 2. Systems proposal report – 30% 3. System design report – 60% |
| 6 July 2026 | Computer Networks |
1. Graded discussion board – 10% 2. Technical report 1 – 30% 3. Technical report 2 – 50% |
| 3 August 2026 | Principles of Machine Learning |
Assessment details TBC |
| 7 September 2026 | Business Data Analytics |
1. Presentation – 20% 2. Written assignment – 30% 3. Written assignment – 50% |
| 5 October 2026 | Project Management and the Computing Professional |
1. Group presentation – 20% 2. Group report – 30% 3. Individual systems proposal – 50% |
| 2 November 2026 | Fundamentals of Artificial Intelligence |
1. Individual report – 30% 2. Individual assignment – 20%% 3. Individual report – 50% |
| 7 December 2026 | Modern Database Systems |
1. Graded discussion board – 10% 2. Presentation – 20% 3. Technical implementation and Query report – 70% |
| 4 January 2027 | Cloud Computing |
1. Graded discussion board – 10% 2. Assignment 1 – 30% 3. Assignment 2 – 60% |
| 1 February 2027 | Information Systems Development |
1. Individual written assignment – 20% 2. Design diagrams and narrative – 20% 3. Technical report with implementation evidence – 60% |
| 1 March 2027 | Software Engineering |
1. Graded discussion board – 10% 2. Systems proposal report – 30% 3. System design report – 60% |
| 5 April 2027 | Computer Networks |
1. Graded discussion board – 10% 2. Technical report 1 – 30% 3. Technical report 2 – 50% |
| 3 May 2027 | Principles of Machine Learning |
Assessment details TBC |
| 7 June 2027 | Business Data Analytics |
1. Presentation – 20% 2. Written assignment – 30% 3. Written assignment – 50% |
| 5 July 2027 | Project Management and the Computing Professional |
1. Group presentation – 20% 2. Group report – 30% 3. Individual systems proposal – 50% |
| 2 August 2027 | Fundamentals of Artificial Intelligence |
1. Individual report – 30% 2. Individual assignment – 20%% 3. Individual report – 50% |
| 6 September 2027 | Modern Database Systems |
1. Graded discussion board – 10% 2. Presentation – 20% 3. Technical implementation and Query report – 70% |
| 4 October 2027 | Cloud Computing |
1. Graded discussion board – 10% 2. Assignment 1 – 30% 3. Assignment 2 – 60% |
| 1 November 2027 | Information Systems Development |
1. Individual written assignment – 20% 2. Design diagrams and narrative – 20% 3. Technical report with implementation evidence – 60% |
| 6 December 2027 | Software Engineering |
1. Graded discussion board – 10% 2. Systems proposal report – 30% 3. System design report – 60% |
| 3 January 2028 | Computer Networks |
1. Graded discussion board – 10% 2. Technical report 1 – 30% 3. Technical report 2 – 50% |
| 7 February 2028 | Principles of Machine Learning |
Assessment details TBC |
| 6 March 2028 | Business Data Analytics |
1. Presentation – 20% 2. Written assignment – 30% 3. Written assignment – 50% |
You can register for your final research modules once you have studied at least seven of the nine taught modules:
|
Module name |
Assessment details |
| Research Development |
1. Literature review – 20% 2. Project plan and enhanced literature review – 80% |
| Research Project |
1. Thesis – 80% 2. Portfolio – 20% |
Across your MSc, you’ll complete a mix of assessments designed to stretch your thinking, strengthen your communication skills, and bring your learning to life. Each module (except your final research modules) includes three assignments – helping you build confidence, test ideas and apply theory in more than one way.
Here’s a snapshot of the main types of assessments you’ll complete across your core modules.
Technical report: produce a detailed, well-structured analysis of a technical problem, solution, or system, often with screenshots, code snippets, or configuration evidence.
Design or implementation project: plan, build, and document a working prototype, model, or system using industry-standard tools and practices.
Case study analysis: evaluate a real or simulated scenario, identify challenges, and propose solutions grounded in computing principles and current best practice.
Discussion board contribution: engage in structured, tutor-led online debates, demonstrating critical thinking, problem-solving, and collaboration.
Portfolio: compile artefacts such as code, diagrams, system models, and explanatory notes to showcase your technical and professional skills.
Ethics or strategy briefing paper: advise an organisation, client, or committee on a complex technology issue, balancing technical, ethical, and commercial perspectives.
Presentation or video demonstration: explain your project or technical findings in a recorded or live presentation, sometimes paired with a live or narrated system demo.
Research dissertation: complete an in-depth research project that tackles a significant computing challenge, presenting your findings, methodology, and technical recommendations in a formal dissertation.
*Please note, module schedule and assessments are subject to change.
Studying online with Walbrook is designed to be flexible and engaging, giving you access to everything you need to succeed:
Full-time students should set aside around 30 hours per week.
You'll start a new 8-week module each month, so while you’re beginning your learning in one module, you’ll be preparing for assessment in the other.
Part-time students should set aside around 17 hours per week.
You'll start a new 8-week module every other month, making it easier to fit your studies around work, family and everyday life.
Your self-study will include:
Engaging programme content delivered via our online study platform.
Case studies and applied tasks that link theory to real business scenarios.
Preparation for assessments including reports, proposals and project work.
Our support is built around you and your success. From enrolment to graduation, you’ll have access to digital academic tools that help you study in a way that works for you, and people who are here to help.
You'll benefit from:
Digital learning materials including key readings, videos, and research resources.
Access to a digital library to support your independent research.
Support to help you stay on track and direct you to the right teams when needed.
Applying to study an online master's at Walbrook is simple, and you can do it directly.
Review our entry requirements to make sure you meet them.
Apply through our secure online application portal and upload your documents as you go.
By paying for your first module (part-time) or first two modules (full-time).
Any questions about our online degrees or studying at Walbrook? Our Enrolment Advisors are here to help.
Our office is open Monday to Friday from 8.00am to 5.30pm UK time (excluding UK public holidays).
The UK tech sector is valued at $1.2 trillion (Tech Nation Report 2025) and growing faster than anywhere else in Europe. Within the tech sector, the World Economic Forum’s Future of Jobs Report 2025 lists Big Data and AI among the fastest-growing skills, creating strong demand for experts who can turn complex datasets into actionable insights.
Our 100% online MSc Computer Science with Data Science prepares you to meet this demand head-on. You’ll graduate with data analytics, machine learning, and data visualisation expertise, backed by strong research skills and the ability to design, secure, and optimise computer systems. Whatever your path – from data scientist to business intelligence leader – you’ll have the essential skills and deep understanding to excel in a competitive, data-driven economy.
Average UK salary: £76,625
Lead complex analytics projects that extract value from vast datasets. As a senior data scientist, you’ll design models, apply advanced machine learning methods, and use data mining techniques to tackle organisational challenges. With expertise in data analytics, data structures, and data security, you’ll be ready to guide strategy and innovation across sectors.
Average UK salary: £76,625
Average UK salary: £51,964
Turn raw data into clear, actionable insights. In this role, you’ll use data visualisation techniques, statistical analyses, and data models to support decision-making at a senior level. Your experience in programming languages, database programming, and exploratory data analysis will help you transform information into strategies that drive measurable results.
Average UK salary: £51,964
Average UK salary: £67,746
Build and deploy intelligent systems that can learn from data. You’ll develop and optimise machine learning solutions, from predictive models to artificial neural networks, ensuring accuracy, scalability, and security. With skills in software engineering, object oriented programming, and operating systems, you’ll bridge the gap between data science research and practical, high-performance applications.
Average UK salary: £67,746
*Salaries listed from glassdoor.co.uk and accurate as of February 2026.
Your MBA is delivered through an online study platform, where you’ll study either one or two modules at a time depending on your study mode. Full-time students take two modules in parallel (with a short gap between start dates), while part-time students complete one module at a time.
Here’s what you can expect:
Weekly learning units to guide your progress
Readings and case studies
Videos and narrated presentations (mini-lectures)
Online discussion forums
Quizzes and tasks to check your understanding
You’ll have the freedom to plan your study time around work and life – but within a guided schedule that helps you stay focused, connected, and on track to succeed.
To get the best learning experience, you’ll need a reliable computer, internet, and audio setup. We recommend a laptop or desktop with at least an Intel i5 processor, 8GB RAM, and 500GB storage (Windows is our primary environment, though you can use Mac or Linux). A stable internet connection (5Mbps download, 2Mbps upload), webcam, and microphone are essential, and we strongly suggest using headphones for online sessions.
For smoother study, extra resources like a second monitor, noise-cancelling headphones, 16GB+ RAM, SSD storage, and an external hard drive are recommended. Walbrook provides access to the required software, though some programmes may ask you to set up a VPN. Our technical support is Windows-based, but you’re welcome to work on Linux or macOS if you prefer.
This master’s degree combines core computing knowledge with advanced data science expertise. You’ll explore data analytics, machine learning algorithms, and data visualisation techniques, while also studying database systems, software development, and cyber security. The programme blends theoretical knowledge with hands-on practice so you can gain skills to help you solve real world problems in a range of industries.
No – this programme is designed for graduates from a non-computing academic background. You'll study modules that cover the fundamental aspects of computer systems, database design, and software development, as well as more advanced areas like statistical data analysis and machine learning algorithms.
As a future data scientist, you’ll need a mix of essential knowledge and practical experience. This MSc builds your ability to work with data manipulation, design and query database systems, and apply machine learning to identify trends and patterns. You’ll graduate able to create solutions that add measurable value to organisations through data-driven decision-making.
Yes – the programme includes dedicated learning on project management for technical environments. You’ll learn how to plan, execute, and oversee projects that involve data science or software development, ensuring they are delivered on time and within budget. This is vital if you want to lead teams or take on more strategic responsibilities in your career.
Graduates often go on to work as data scientists, data analysts, or machine learning specialists. Your broad spectrum of skills – from database design and data mining algorithms to software development and cloud computing platforms – will open opportunities in industries ranging from finance and healthcare to technology and investment management.
Yes – both home and international students are welcome to apply. If your first language isn’t English, you’ll need to meet our English language requirements – further information can be found in the 'entry requirements' section above. This 100% online MSc allows you to study from anywhere in the world, connect with a diverse network of fellow students, and develop the data science skills to excel in a global job market.
Graduate in 14 months full-time, or flex to part-time.
Ranked 12th for employment outcomes in the UK*
Total fees: £7,680 – pay in full or pay per module.
*National Graduate Outcomes Survey, 2024