MSc — 2026 entry Data Science (Conversion)
Unlock your potential with our new MSc Data Science (Conversion) programme, created especially for students from non-STEM backgrounds. Build in-demand skills in big data analytics, AI, cloud computing, data ethics and security, all while learning from leading academics and gaining exposure to real industry challenges. Whether you’re aiming for a career change or looking to boost your prospects, this programme gives you the tools to shape tomorrow’s technology landscape.
4,138+ people have created a bespoke digital prospectus
Why choose
this course?
- Develop industry-relevant data science skills through a programme co-designed with industry and informed by leading research.
- Upskill or retrain with our Data Science (Conversion) MSc if you come from a varied academic or professional background.
- Transition into the data science workforce through a clear pathway designed for career changers, working professionals and international learners.
- Study flexibly through full-time or part-time options designed to fit around work and other commitments. The two modes aim to cater for various professional backgrounds, with guidance available on the mode best suited to you.
The demand for data science professionals continues to grow across industries such as finance, banking, politics and healthcare due to the increasing reliance on AI and data-driven decision-making.
Statistics
Fantastic graduate prospects
95% of computer science graduates are in work or further education (Graduate Outcomes 2025, HESA)
Top 10 in the UK
4th in the UK for overall satisfaction in information technology (National Student Survey 2025)
Excellent global ranking
7th in the UK and Top 75 globally for computer science and engineering (Shanghai Global Ranking of Academic Subjects 2025)
What you will study
Start your journey into data science by developing the essential mathematics and programming skills that underpin the core modules of the programme. Gain experience working with real-world datasets across the entire data analysis pipeline while building strong technical knowledge in modern machine learning and statistical methods and their application in business contexts.
The course covers key practical topics, such as business analytics and data visualisation, data security, building databases and working with cloud-based technologies. You will also have the opportunity to dive deeper into specialist areas such as Natural Language Processing, Deep Learning, and other advanced AI methods, allowing you to shape your expertise in this dynamic and transformative field.
You will complete a dissertation where you can further explore an area of personal interest under the guidance of an academic supervisor. Dissertation projects focus on topical, real-world problems and are often linked to cutting-edge research. Through this process, you will develop research skills, learn how to communicate effectively, and engage with the ethical and security considerations central to data science.
If you're studying this course full-time, you'll study eight modules across the year — four in each semester. You will work on your project full-time during the summer period for approximately two-and-a-half months.
If you are studying part-time, you will study four modules across the year, two in each semester. You will work on your project during the summer period over the two years.
The structure of our programmes follows clear educational aims that are tailored to each programme. These are all outlined in the programme specifications which include further details such as the learning outcomes:
Teaching and learning
Our teaching is influenced by current research in data science and artificial intelligence (AI) and driven by the tools and techniques that both employers and academic researchers are using daily.
You will be taught by lecturers who are experts in their fields and are members of the Surrey Institute for People-Centred AI and/or the NICE Research group.
You will also benefit from guest lectures, industry talks and seminars.
- Seminars
- Lectures
- Workshops
- Laboratory work
- Group work
- Project work
- Research work
- Tutorials
- Independent study
AssessmentWe use a variety of methods to assess you, including:
- Coursework
- Examinations
- Presentations
- Projects (individual and group)
- Reports
- Class tests.
General course information
Contact hours
Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.
Timetable
New students will receive their personalised timetable during Welcome Week. In later semesters, at least one week before the start of the semester.
Scheduled teaching can take place on any day of the week (Monday – Friday), with part-time classes normally scheduled for one or two days. Wednesday afternoons tend to be for sports and cultural activities.
View our code of practice for the scheduling of teaching and assessment (PDF) for more information.
Location
This course is based at Stag Hill campus. Stag Hill is the University's main campus and where the majority of our courses are taught.
We use a variety of methods to assess you, including:
- Coursework
- Examinations
- Presentations
- Projects (individual and group)
- Reports
- Class tests.
Contact hours
Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.
Timetable
New students will receive their personalised timetable during Welcome Week. In later semesters, at least one week before the start of the semester.
Scheduled teaching can take place on any day of the week (Monday – Friday), with part-time classes normally scheduled for one or two days. Wednesday afternoons tend to be for sports and cultural activities.
View our code of practice for the scheduling of teaching and assessment (PDF) for more information.
Location
This course is based at Stag Hill campus. Stag Hill is the University's main campus and where the majority of our courses are taught.
We offer careers information, advice and guidance to all students whilst studying with us, which is extended to our alumni for three years after leaving the University.
We offer careers information, advice and guidance to all students whilst studying with us, which is extended to our alumni for three years after leaving the University.
Our data science masters graduates are in high demand across many sectors, and go on to roles such as data scientist, data analyst, data engineer, data architect or business analyst.
Surrey graduates have joined organisations such as:
- Allianz Partners
- Bank of America
- Fluro
- Healthera
- IBM
- KPMG
- NBCUniversal
- Rolls-Royce
- S&P Global.
- A multi-purpose Computer Science Laboratory. View a video tour
- Six open access PC labs and four dedicated specialist labs
- Specialist desktop solutions, including development software, research packages and dedicated printing.
- On premise cloud facilities, OpenNebula provides large-scale support for deployment and security experimentation
- State-of the art machines are grouped into an AI cluster to support performing high level computer experimentation.
UK qualifications
A minimum of a 2:2 UK honours degree in any subject, with prior study of modules in mathematics, statistics, or programming.
We may be able to take relevant work experience into consideration if you don't meet these requirements. If this is the case, please provide full details of your role and responsibilities in your personal statement and CV.
English language requirements
6.5 overall including 6.0 in Writing and 5.5 in each other component
These are the English language qualifications and levels that we can accept.
If you do not currently meet the level required for your programme, we offer intensive pre-sessional English language courses, designed to take you to the level of English ability and skill required for your studies here.
International Pre-Masters
Prepare for postgraduate study and boost your career prospects. This is an intensive programme of academic subjects, study skills and English language preparation designed to help you succeed.
Recognition of prior learning
We recognise that many students enter their course with valuable knowledge and skills developed through a range of ways.
If this applies to you, the recognition of prior learning process may mean you can join a course without the formal entry requirements, or at a point appropriate to your previous learning and experience.
There are restrictions for some courses and fees may be payable for certain claims. Please contact the Admissions team with any queries.
Fees per year
Explore UKCISA’s website for more information if you are unsure whether you are a UK or overseas student. View the list of fees for all postgraduate courses.
September 2026 - Full-time - 1 year
- UK
- £12,900
- Overseas
- £25,900
September 2026 - Part-time - 2 years
- UK
- £6,500
- Overseas
- £13,000
- These fees apply to the academic year 2026-27 only. Fees are reviewed annually, and tuition fees may increase for courses running over more than one year.
Payment schedule
- Students with Tuition Fee Loan: the Student Loans Company pay fees in line with their schedule (students on an unstructured self-paced part-time course are not eligible for a Tuition Fee Loan).
- Students without a Tuition Fee Loan: pay their fees either in full at the beginning of the programme or in two instalments as follows:
- 50% payable 10 days after the invoice date (expected to be October/November of each academic year)
- 50% in January of the same academic year.
- Students on part-time programmes where fees are paid on a modular basis: cannot pay fees by instalment.
- Sponsored students: must provide us with valid sponsorship information that covers the period of study.
The exact date(s) will be on invoices.
Funding
You may be able to borrow money to help pay your tuition fees and support you with your living costs. Find out more about postgraduate student finance.
Admissions information
Once you apply, you can expect to hear back from us within 14 days. This might be with a decision on your application or with a request for further information.
Our code of practice for postgraduate taught admissions explains how the Admissions team considers applications and admits students. Read our postgraduate applicant guidance for more information on applying.
About the University of Surrey
Need more information?
Contact our Admissions team or talk to a current University of Surrey student online.
Terms and conditions
When you accept an offer to study at the University of Surrey, you are agreeing to follow our policies and procedures, student regulations, and terms and conditions.
We provide these terms and conditions at offer stage and are shown again at registration. You will be asked to accept these terms and conditions when you accept the offer made to you.
View our generic registration terms and conditions (PDF) for the 2025/26 academic year, as a guide on what to expect.
Disclaimer
This online prospectus has been published in advance of the academic year to which it applies.
Whilst we have done everything possible to ensure this information is accurate, some changes may happen between publishing and the start of the course.
It is important to check this website for any updates before you apply for a course with us. Read our full disclaimer.
Subject to validation
This programme is subject to approval. This means that it has received initial agreement from the University and is currently undergoing a detailed final approval exercise, through the University’s quality assurance processes.
These processes are a requirement for all Higher Education Institutions within the UK, to ensure that programmes are of the highest standard. Occasionally there may be instances where the University may delay or not approve the introduction of the programme.