UCAS code | 1234 |
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Duration | 1 year full time 2 years part time |
Entry year | 2025 |
Campus | Streatham Campus |
Discipline | Data Science and Analytics |
Contact | Web: Enquire online |
Typical offer | A good degree (normally a 2:2). |
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UCAS code | |
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Duration | 2 years full time |
Entry year | 2025 |
Campus | Streatham Campus |
Discipline | Data Science and Analytics |
Contact | Web: Enquire online |
Typical offer | A good degree (normally a 2:2). |
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Overview
- Designed for those wanting to work with and derive meaning from data, but without prior experience of programming
- Explore a wide variety of applications to prepare you for a career working with data in a wide variety of sectors
- Graduate with the capability to extract otherwise-hidden information within data and use it to make informed decisions, with the skills needed to enter a Data Scientist or Analyst role
- Learn a variety of languages essential to Data Science, including R and Python
- Work with data and gain the ability to perform statistical analysis to answer questions, and understand how to interpret and communicate results in the presence of bias and uncertainty.
Top 20 in the UK for Mathematics and Computer Science
18th for Mathematics and 19th for Computer Science in the Complete University Guide 2025
Partner to 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
Exeter's Q-Step Centre for Applied Social Data Analysis integrates cutting-edge quantitative methods with substantive, real-world social science issues
Entry requirements
A good degree (normally a 2:2) in a numerate subject.
Relevant numerate degrees: Maths; Physics; Computer Science; Data Science; Engineering; Bioscience; Chemistry; Economics; Accounting; Finance.
Successful applicants will usually have at least an A-level or equivalent in Mathematics and/or have received quantitative skills training as part of their undergraduate programme or professional experience.
Prior experience of coding is not necessary on this course.
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 test scores for this course fall under Profile B3. Please visit our English language requirements page to view the required test scores and equivalencies from your country.
"The course was an extensive coverage of data science and stats, with lots theoretical and practical learning. All the lecturers I had were fantastic. They were always very willing to help, super approachable and really friendly. It was so nice to be able to feel like I had a proper relationship with them.
My dissertation supervisors were the best supervisors I could’ve asked for. They’d help whenever and always provided brilliant guidance allowing me to do my best.
Now I’ve graduated I’m working at Mazars as a Data Analyst. It’s been really nice to use the things I learnt during my masters in my career, and I’ve felt unbelievably well prepared going into my professional life."
Matt
MSc Applied Data Science and Statistics graduate
Course content
Teaching on this programme is delivered through a mix of lectures, projects, group work and hands-on lab sessions. Many of your lectures will be interactive combining a blend of classroom learning, coding and data analysis. Group and individual projects will be undertaken using real data and will often focus on topical challenges which are the focus of current research.
Assessments will be based on a combination of exams, group and individual project work, practical data analysis, visualisation and communication skills.
The course is based around open source software. As a student you will also have access to many programmes, such as Matlab, through the University.
All aspects of the course are design with windows, mac and linux in mind. Many of your practical sessions will take place in the department’s newly refurbished mac suites.
The taught component of the programme is completed in June with the project extending over the summer period for submission in September.
The modules we outline here 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.
Compulsory modules
Code | Module | Credits |
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MTHM501 | Working with Data | 15 |
MTHM502 | Introduction to Data Science and Statistical Modelling | 15 |
MTHM503 | Applications of Data Science and Statistics | 15 |
MTHM507 | Communicating Data Science | 15 |
MTHM017 | Advanced Topics in Statistics | 15 |
MTHM506 | Statistical Data Modelling | 15 |
MTHM505 | Data Science and Statistical Modelling in Space and Time | 15 |
SOCM033 | Data Governance and Ethics | 15 |
MTHM504 | Applied Data Science and Statistics Project | 60 |
This module will provide you with extensive practical work that is of direct relevance to your development as an experienced professional. You will get the chance to apply the knowledge and skills you have acquired from taught modules to authentic problem solving in the work place. Collaborating with your work placement employer, you will identify a project that will constitute your MSc dissertation. Ideally, the dissertation should be based on the work that you will undertake during the placement, but this is not compulsory.
MSc Project/Dissertation
This dissertation will give you the chance to demonstrate your knowledge, to exercise your initiative and personal responsibility, and to use the research techniques and skills you have developed throughout your degree.
You will be required to solve a research or industrially-related practical problem based on the topics learned within, but not exclusive to, the MSc programme you are registered for. The project work will lead to a major piece of work (dissertation) of approximately 15,000 words (max. 80 pages, including references and appendices) that involves project planning, analytical, experimental or empirical results and their interpretation, showing how the goals of the project have been met. You will receive a list of potential projects and will be required to express your two preferences. Alternatively, you can discuss your own dissertation ideas with the module leader / potential supervisor (academic staff) with a view to explore if they offer required technical rigour and research challenge. You will be encouraged to discuss your preferences with relevant academic staff before we allocate projects. As part of the research project, you are expected to undertake a considerable amount of self-study. There is no formal taught component in the module, apart from suggested regular meetings with the supervisor.
Prerequisite modules: All compulsory modules listed for (or equivalent) the MSc programme you are registered for.
Course variants
- Combine your masters in Applied Data Science and Statistics with work experience in the UK, putting your learning into practice while studying
- Studied over two years, you’ll have the opportunity to gain valuable professional experience by completing a 9-12month work placement in a role relevant to your degree
- Become a sought-after professional with strong industry experience
Fees
2025/26 entry
UK fees per year:
£14,300 full-time
With Professional placement (second year) £2,860 full-time
International fees per year:
£30,300 full-time
With Professional placement (second year) £6,060 full-time
Scholarships
We invest heavily in scholarships for talented prospective Masters students. This includes over £5 million in scholarships for international students, such as our Global Excellence Scholarships*.
For more information on scholarships, please visit our scholarships and bursaries page.
*Selected programmes only. Please see the Terms and Conditions for each scheme for further details.
Teaching and research
The programme will include applications across a wide variety of sectors and help you develop innovative and responsible approaches to the use of data. You will cover the entire spectrum from collection through to interrogation and analysis, interpretation, visualisation, and communication.
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.
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 is easy to consult individual members of staff or to fix appointments with them via email. As a friendly group of staff, you will get to know us well during your time here.
Careers
Employer demand for statistically-trained data scientists is high. A staggering 98% of our 2016/17 computing graduates, and 84% of mathematics graduates, went into work or further study within six months of graduation.
A World Economic Forum report ‘The Future of Jobs’ states that data analysts are likely to be one of two job fields which will be critically important across all industries and geographies by 2020. ‘Companies expect that [data analysts] will help them make sense and derive insights from the torrent of data generated by technological disruptions’.
Graduate destinations
Whether you’re looking to take your career in a new direction or for an MSc that will sit alongside your undergraduate degree to land you an exhilarating graduate job, you’re unlikely to find a better choice than Applied Data Science and Statistics.
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.