Data Science and Analytics MSc

Course overview

We’re surrounded by data. The variety and amount we collect and store grows every day, from the simplest of retail transactions to the complex and intimate medical records of millions.

There is an increasing demand for people who can manage, control and provide insight into the way data is used. These individuals require an understanding of computer science and mathematics, as well as a familiarity with the data needs and processes of a number of different areas, including healthcare, business, government and the environment.

Our Data Science and Analytics Masters degree offers you the opportunity to develop a range of relevant skills including:

• analysing structured and unstructured data
• analysing large datasets
• critically evaluating results in context
• getting insights from data

The course combines expertise from the Schools of Computing, Geography and Mathematics with that of Leeds University Business School.

This collaboration allows you to benefit from a range of data science perspectives and applications, allowing you to tailor the course to match your own career ambitions.

Why study at Leeds:

• Our globally-renowned research conducted right here on campus feeds directly into the course, shaping your learning with the latest thinking in areas such as probability and financial mathematics, modern applied statistics and analysis.
• Benefit from our School’s close links with organisations like Leeds Institute for Data Analytics, Leeds Institute for Fluid Dynamics and the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.
• Advance your knowledge and skills in key areas of data science, both theoretically and practically.
• Tailor the degree to suit your specific interests with a broad selection of optional modules to choose from such as machine learning, programming and GIS.
• Put theory into practice by conducting a project which focuses on a real-world problem, giving you the chance to apply the knowledge acquired throughout the course and demonstrate independent research skills necessary for a professional or academic career.
• Access excellent teaching facilities and computing equipment throughout the school, complemented by social areas and communal problem-solving spaces.
• Experience expert theoretical and practical teaching delivered by a programme team made up of academics from the Schools of Mathematics, Computing, Geography and Business.

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Study online

We also offer a fully online Data Science (Statistics) MSc, covering an extensive range of in-demand data skills such as data acquisition, data preparation, data wrangling, modelling and analysis, and how to deal with missing data.

Course details

The course will equip you with the knowledge and skills you need to meet the challenges of data science in the modern world.

You can choose modules from the School of Mathematics, the School of Computing, the School of Geography and Leeds University Business School.

Mathematics modules are available for students who are not from a mathematics/statistics background, while computing modules will be suitable for students on this programme who are not from a computer science background.

The course will introduce you to different perspectives on data science, including the mathematical and computational underpinnings of the subject and its applications in specific contexts.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.

For more information and a full list of typical modules available on this course, please read Data Science and Analytics MSc in the course catalogue

Compulsory modules

Data Science –15 credits

This module gives you an insight into some general principles of the work of a data scientist and teaches you some of the underpinnings of artificial intelligence and statistics in the practice of data science.

Learning Skills through Case Studies –15 credits

This module will develop your skills for your dissertation, potential further research, and employment. This will include presentation skills and teamwork, some of which will be developed through real-life case studies.

Dissertation in Data Science and Analytics – 60 credits

The dissertation gives you the opportunity to demonstrate independent research skills necessary for a professional or academic career. It allows you to deepen your knowledge and understanding of practical issues whilst applying skills acquired throughout the programme.

The list of topics to choose for your project is wide-ranging, dealing with a real-world problem. It will typically require a literature review, project planning, data collection, analysis and interpretation. Many recent projects have involved co-supervision with the Leeds Clinical Trials Unit, Leeds Institute for Data Analytics (LIDA) and the MET office.

It is possible to involve an industrial partner in your dissertation, subject to the approval of the programme manager. We would expect students interested in partnering with industry to have an existing connection with their partner of choice.

Optional modules

Please note: The modules listed below are indicative of typical options.

Click here if you’d like to see the full range of options.

• Information Visualization – 10 credits
• Knowledge Representation and Reasoning – 15 credits
• Machine Learning – 15 credits
• Deep Learning – 15 credits
• Programming for Data Science – 15 credits
• Data Mining and Text Analytics – 15 credits
• Geographic Data Visualisation & Analysis – 15 credits
• Geodemographics and Neighbourhood Analysis – 15 credits
• Big Data and Consumer Analytics – 15 credits
• Predictive Analytics – 15 credits
• Applied GIS and Retail Modelling – 15 credits
• Business Analytics and Decision Science – 15 credits
• Forecasting and Advanced Business Analytics – 15 credits
• Machine Learning in Practice – 15 credits
• Mixed Models – 10 credits
• Linear Regression and Robustness – 15 credits
• Statistical Theory – 15 credits
• Time Series – 10 credits
• Generalized Linear Models – 10 credits
• Mixed Models with Medical Applications – 15 credits
• Linear Regression and Robustness and Smoothing – 20 credits
• Statistical Theory and Methods – 15 credits
• Statistical Learning – 15 credits
• Multivariate Methods – 15 credits
• Multivariate and Cluster Analysis – 15 credits
• Time Series and Spectral Analysis – 15 credits
• Generalised Linear and Additive Models – 15 credits
• Statistical Computing – 15 credits
• Transport Data Science – 15 credits

Learning and teaching

Teaching is through lectures, tutorials, seminars and supervised research projects. Extensive use is made of IT and a wide range of materials are available to enhance and extend the material taught formally.

Programme team

Programme leader Dr Luisa Cutillo's current research interests are related to networks and networks applications. In particular, she is interested in studying and validating networks structures and in biomedical networks application. Additionally, Dr Cutillo is one of the Women in Machine Learning Bords of Directors, a worldwide organization aimed at empowering women in the field of machine learning.

On this course, you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Assessment

Assessment is by a range of methods, including formal examination, assignments, coursework, reports and practical activities.

Applying

Entry requirements

A bachelor degree with a First or high 2:1 (hons) in a subject containing a substantial mathematical, statistical and/or computing component. You should have strong grades in all your key modules (mainly Firsts with no key marks below 2:1).

You must provide a list of the type and level of maths/computing modules that you have studied if this is not obvious from your transcript. We may ask for further detailed module information if these are not clear on your transcript.

We do not normally accept degrees in accountancy or finance for this MSc.

Please note: this is an extremely popular MSc and places are limited. You may be interested in applying for these data science and analytics degrees:

• Advanced Computer Science (Data Analytics) MSc
• Air Quality Solutions with Data Science MSc
• Data Science (Statistics) MSc
• Environmental Data Science and Analytics MSc
• Geographical Information Science MSc
• Urban Data Science and Analytics MSc

We accept a range of international equivalent qualifications. For more information please contact the Admissions Team.

English language requirements

IELTS 6.5 overall, with no less than 6.0 in all components. For other English qualifications, read English language equivalent qualifications.

Improve your English

International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.

This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks). 

We also offer online pre-sessionals alongside our on-campus pre-sessionals. Find out more about our six week online pre-sessional.

You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.

How to apply

Application deadlines

Please read our How to Apply page for full details, including application deadlines and what to include with your application.

Applicants are encouraged to apply as early as possible.

30 June 2025 – International applicants

12 September 2025 – UK applicants

Click below to access the University’s online application system and find out more about the application process.

If you're still unsure about the application process, contact the admissions team for help.

Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

Admissions policy

University of Leeds Admissions Policy 2025

This course is taught by

School of Mathematics
Leeds University Business School
School of Computer Science
School of Geography

Contact us

School of Mathematics Admissions Team

Email: maths-msc@leeds.ac.uk
Telephone:

Fees

UK: £14,750 (Total)

International: £33,750 (Total)

Read more about paying fees and charges.

For fees information for international taught postgraduate students, read Masters fees.

Additional cost information

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

Career opportunities

There is an increasing demand for individuals who can manage and control the way data is used. These individuals require an understanding of computer science and mathematics as well as a range of sector-specific skills.

The emerging era of ‘big data’ brought about by the digital technology revolution shows no signs of abating. With the modern world producing ever-growing amounts of new information, data scientists will become increasingly important to help governments, businesses, researchers, NGOs and many other organisations make sense of it all.

Plus, University of Leeds students are among the top 5 most targeted by top employers according to The Graduate Market 2024, High Fliers Research.

Here’s an insight into some of the job positions and organisations previous data science graduates have secured:

• Product SME, Shell UK
• Senior Software Engineer, London Stock Exchange Group (LSEG)
• Data Integration Lead, Stainless Games

Careers support

At Leeds, we help you to prepare for your future from day one. We have a wide range of careers resources — including our award-winning Employability teamEmployability Team who are in contact with many employers around the country and advertise placements and jobs. They are also on hand to provide guidance and support, ensuring you are prepared to take your next steps after graduation and get you where you want to be.

• Employability events — we run a full range of events including careers fairs in specialist areas and across broader industries — all with employers who are actively recruiting for roles.
• MyCareer system — on your course and after you graduate, you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.
• Qualified careers consultants — gain guidance, support and information to help you choose a career path. You’ll have access to 1-2-1 meetings and events to learn how to find employers to target, write your CV and cover letter, research before interviews and brush up on your interview skills.
• Opportunities at Leeds — there are plenty of exciting opportunities offered by our Leeds University Union, including volunteering and over 300 clubs and societies to get involved in.

Explore more about your employability opportunities at the University of Leeds:

Find out more about career support.