Course overview
Master the science behind data and become a confident analytical decision-maker
The MSc Data Science (Statistics), delivered in collaboration with the School of Mathematics and the Leeds Institute for Data Analytics (LIDA), is a flexible fully-online Masters degree delivered by a World Top 100 University (QS 2027), designed for graduates and professionals who want to go beyond using data tools to understanding the science behind data-driven decision-making.
As organisations increasingly rely on data, artificial intelligence and machine learning to inform strategy, there is growing demand for professionals who can not only analyse data but also evaluate evidence, quantify uncertainty and communicate trusted insights. This programme combines advanced data science skills with rigorous statistical training, enabling you to develop the analytical depth needed to make confident decisions in complex real-world environments.
Unlike many data science programmes that focus primarily on technologies and techniques, this course places statistical expertise at the heart of your learning. You'll develop a deep understanding of the methods that underpin modern analytics, machine learning and data science, building expertise in statistical modelling, inference, computation and data interpretation.
Develop practical capabilities across the full data lifecycle
Designed for graduates with a strong quantitative background, as well as professionals seeking to advance or transition into data-focused careers, this programme develops practical capabilities across the full data lifecycle, from data acquisition, preparation and visualisation through to modelling, analysis and communication.
Drawing on expertise from the School of Mathematics and the Leeds Institute for Data Analytics (LIDA), you'll explore cutting-edge developments in statistics and data science while working on projects inspired by real-world challenges. Application areas may include health, retail, urban analytics, climate and weather, artificial intelligence and emerging digital technologies, providing experience that is relevant across a wide range of sectors, and industry-specific data lifecycles.
Enhance your data storytelling skillset
Throughout your studies, you'll develop both technical expertise and the ability to communicate findings effectively through the method of data storytelling. Employers increasingly seek professionals who can influence decision-making, not simply analyse data.
Through reports, presentations, visualisations and project work, you'll learn how to transform complex analysis into meaningful recommendations through a data storytelling approach tailored to both technical and non-technical audiences. This will ensure the data that you present is optimised for organisations to act upon, delivering real-world impact.
Study from anywhere in the world with this fully online degree
Accessible worldwide and designed to fit around professional and personal commitments, this fully online Masters degree allows you to gain an internationally recognised qualification from the University of Leeds while continuing your career. Whether you want to deepen your expertise, progress into leadership roles or prepare for a career change, you'll graduate with the statistical depth, data science knowledge and decision-making skills needed to thrive in an increasingly data-driven world.
Learner story: Floe Foxon
Discover how Floe Foxon enjoyed ‘sense of control’ over his studies on the online Data Science (Statistics) MSc.
Course highlights
- Gain a Masters in Data Science (Statistics) from a World Top 100 University (QS World Rankings 2027).
- Develop a comprehensive understanding of key statistical methods and their practical applications across industries.
- Build specialist expertise in specialised topics within statistics such as Bayesian modelling, Monte Carlo estimation and dimension reduction.
- Learn to apply statistical tools and techniques tailored for real-world challenges.
- Complete a practical data analysis project that develops transferable skills and showcases independent working ability.
- Build proficiency in key programming languages and techniques for data analysis.
- Master strategies for analysing both traditional “simple random sample” and complex “big data” population datasets.
- Work confidently with large, high-dimensional datasets, including those with more variables than observations).
- Understand ethical, legal and governance issues relating to data gathering and analysis, evaluating their impact on decision-making.
- Benefit from research-led teaching drawing on expertise from the Leeds Institute for Data Analytics, a leader in data science innovation.
- Study flexibly online, gaining the skills and knowledge needed to advance your career in data science and statistics.
Course details and modules
You'll study core material in data science and statistics before moving on to more advanced topics including linear modeling, Bayesian statistics and statistical computing.
You’ll put the advanced theories you’re learning into practice by solving real-world problems with support from the Leeds Institute for Data Analytics and the School of Mathematics. The results of your work across courses and projects will include examples of data analysis that can be presented to potential employers, which will demonstrate that you have the skills for data-driven senior roles in business, government, and nonprofit sectors.
From your time on the programme, you’ll understand how your data knowledge can be applied to current and future statistical challenges at local, national and international levels.
Course structure
In your first year, you will typically study three modules from the Foundation carousel, as well as three modules from the Development carousel.
In your second year, you will typically study the remaining three modules from the Development carousel as well as three modules from the Advanced carousel.
Foundation carousel
Programming for Data Science (15 credits)
Build a firm foundation in programming in Python for data science. Whether you are new to Python or an experienced Python user, you will become a confident programmer. able to independently translate a broad range of data science related problems into functioning computer programs and communicate the results.
Statistical Methods (15 credits)
This comprehensive introduction to statistical thinking and data analysis including probability rules and distributions, methods of estimation and hypotheses testing present the basics of Bayesian inference.
Exploratory Data Analysis (15 credits)
Take an introduction to basic data analysis techniques, which can be used to perform a preliminary investigation of data sets. Exploring this data involves visualising the variables and relationships to help determine outliers, identify trends, suggest suitable statistical models and inform future data gathering.
Development carousel
Project Skills (15 credits)
Equip yourself with the skills necessary to undertake project work as a data scientist. Project planning, reviewing existing methodologies and the presentation of outputs in different forms all form part of this. You will also understand the ethical considerations of data usage.
Machine Learning (15 credits)
Delve into the complexities of machine learning, a rapidly developing research area which takes an algorithmic approach to identifying patterns and statistical regularities in data without or with limited human intervention, often with the aim of supporting decision making. You will learn to apply a number of machine learning techniques that are widely used in industry, government, and other large organisations.
Linear Modelling (15 credits)
Understand the theory of linear models and be able to fit multiple linear regression models to data and interpret the results. The content will develop your appreciation of the limitations of linear models and the use of link functions to generalise the linear regression model.
Statistical Learning (15 credits)
Understand how statistical learning is at the core of the modern world, translating data into knowledge. Online advertising, automated vehicles, stock market trading, transport planning all use statistical models to learn from past data and make decisions about the future. Statistical learning is a way to rigorously identify patterns in data and to make quantitative predictions.
Data Science (15 credits)
Understand methods of analysis that allow you to gain insights from complex data. The module covers the theoretical basis of a variety of approaches, placed into a practical context using different application domains.
Multivariate Methods (15 credits)
You will explore how statistical methods are utilised to make sense of data with multiple variables, also sometimes called multi-dimensional data, and how to discover patterns and infer valuable information from such data.
Advanced carousel
Capstone Project (15 credits)
You will plan, carry out and present the results of a short project in data science. The project will be presented in a professional format that could serve as an exemplar of your work for a future employer or client.
Statistical Computing (15 credits)
Learn the ability to apply standard methods for random number generation and apply different Monte Carlo methods and develop understanding of the principles and methods of stochastic simulation.
Bayesian Statistics (15 credits)
Take an introduction to Bayesian statistical methods through the consideration of philosophical differences with traditional statistical procedures and the application of Bayesian techniques. You will also be introduced to the ideas of quantitative decision theory and rational decision making.
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.
Learning and teaching
A global learning network
You will have the opportunity to connect with faculty and students through live and asynchronous online content including activities, discussions, readings, and tutoring.
Access a wealth of mathematics expertise and data research
You’ll have the chance to learn from researchers who are actively involved with Leeds Institute for Data Analytics, The Alan Turing Institute and other institutes that have strong industry connections. This means you'll be learning the latest innovations in mathematics based on real-world issues happening right now, equipping you with the most up-to-date and industry-relevant knowledge.
Learning material
You will have access learning material via on-demand videos or interactive transcripts. You can pace yourself through the learning material before engaging in related discussions with faculty and peers.
Flexible, career-focused learning
We recognise that people have busy lives, so our fully online MSc enables you to gain a global health degree online from a world-leading institution—without the added cost of relocating.
Study planners and progress-tracking tos will support your learning, helping you balance your studies with other commitments.
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
Assessments are designed to help you demonstrate the knowledge and practical skills gained throughout each module. Typically, each 15-credit module includes one to two assessments, which may be formative or summative, and are integrated alongside teaching over the study period.
Assessment methods include a variety of formats such as quizzes, written assignments, data analysis projects, programming exercises, and case study reports. These assessments not only test your understanding of statistical theories and data science techniques but also develop essential skills in communication, critical thinking, and independent research.
You will complete your assessments fully online, allowing flexibility to manage your studies alongside professional and personal commitments. The results of your work can also be showcased as evidence of your capabilities to potential employers, supporting your progression into senior roles in data-driven industries.
Applying
Entry requirements
Standard Entry
You must have a 2.2 or above honours degree in a mathematical, computational, engineering or other numerate discipline, including but not limited to:
- Mathematics, Statistics, Physics
- Computer Science, Data Science, AI
- Engineering
- Economics or quantitative Social Sciences
Your degree should include at least one numerate or programming-related module.
Professional Entry
You are eligible through this route if you meet at least one of the following:
- A third-class degree in any discipline plus 1 year of relevant professional experience
- At least 3 years of relevant professional experience in a technical, analytical or digital role
Relevant experience includes, but is not limited to data analysis, coding, automation, software testing, reporting, digital transformation, or any role involving analytical or technical problem-solving duties.
Additional Information
- A short numeracy or programming readiness task may be required
- Professional certifications in data, cloud, coding or AI strengthen your application
Progression
Once you begin your studies, you will need to achieve a pass (50% weighted average or higher) in both of the first two degree modules: Programming for Data Science and Statistical Methods, to continue with the rest of the programme.
If you do not achieve a pass, you will not be able to continue and will be withdrawn from the degree. You will be refunded for any modules you've paid for but haven't yet started.
Proof of your English Language Proficiency
Proficiency in English language is essential to study at the University of Leeds. You will need either:
Alternative English Language Qualification
A degree taught in English from a recognised institution, lasting at least two years at the undergraduate level or one year at the Masters level, which can be evidenced by transcripts and/or certificates.
For more details, contact our Enrolment Advisors at onlineadmissions@leeds.ac.uk
English language requirements
IELTS 6.5 overall, with no less than 6.0 in any component. . For other English qualifications, read English language equivalent qualifications.
How to apply
The ‘Apply’ button at the top of this page takes you to the University's online application system, where you can start your application for this course.
Please see our How to Apply page for information about application deadlines.
Identification
The University of Leeds requires all applicants for fully online programmes to provide proof of their identity at the point of application. Accepted forms of ID are:
- Passport photo page or
- Driving licence or
- National identity card
Admissions policy
University of Leeds Admissions Policy 2027
Contact us
Online Admissions team
Email: onlineadmissions@leeds.ac.uk
Telephone: +44 113 519 8809
Fees
UK: £15,000 (Total)
International: £15,000 (Total)
Fees for 2026/27 academic year of entry (1 September 2026 to 31 August 2027):
UK and International: £15,000 (£1,250 per course, per 15 credit course)
You won’t be billed upfront for the whole degree. Instead, pay as you go - each time you take a course, you’ll pay the tuition just for that course, unless your fees are paid directly by your employer or sponsor. Please note - students in receipt of a loan will be required to complete the programme in 24 months.
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
University of Leeds alumni (or graduates of affiliated institutions)
Alumni are entitled to a 10% bursary towards tuition fees. Find out more about eligibility for the alumni bursary and how to apply.
UK government student loan
UK students may be eligible for a UK government-backed loan, with specific terms and conditions for online courses. Applications are made through the Student Loans Company. Visit the UK Government website to find out more.
Career opportunities
As a graduate of this programme, you’ll be ready for senior roles as a data analyst, data analytics manager, data scientist, statistician, data engineer, business analyst, and more. You’ll have new skills for self-direction and evaluation, managing project work, engaging critically with sources and methods, and evaluating and analysing data.
Top 10 most targeted for 10+ years
by the UK’s leading employers
Careers support
The University of Leeds Careers Service offers extensive online resources to help you maximise your studies and achieve your career goals:
- One-to-one support from a careers advisor via telephone or virtual meeting
- Online career workshops, webinars and resources
- A database of job opportunities and online employer events
- LinkedIn Learning platform
- CV writing tips and job application support
- Interview coaching and practice sessions.
The Careers Service also connects students seeking to work in a specific region, and offers professional development through alumni network, online support and employer partnerships. Find out more about Careers support