Data Science (Statistics) MSc
Year of entry 2025
- Start dates
- September 2024
- March 2025
- September 2025
- Delivery type
- Online exclusive
- Duration
- 24 months part time
- Entry requirements
- Full entry requirements
- English language requirements
- IELTS 6.5 overall, with no less than 6.0 in any component.
- UK fees
- £15,000 (Total)
- International fees
- £15,000 (Total)
- Contact
- onlineadmissions@leeds.ac.uk
Course overview
Developed in collaboration with the School of Mathematics and the Leeds Institute for Data Analytics, our online Data Science (Statistics) masters degree offers you the opportunity to learn in-demand data skills such as data acquisition, data preparation, data wrangling, modelling and analysis, and how to deal with missing data.
Whether you have an undergraduate degree in a quantitative subject with substantial elements of mathematics and statistics or already working in a data-driven STEM field, you’ll be ready for business-critical senior roles in healthcare or environmental science.
The MSc Data Science (Statistics) offers a comprehensive curriculum that spans from foundational data science courses to specialised statistics courses. You'll also learn industry best practices and study widely used methods to understand and interpret data in a range of contexts. Because employers are looking for job candidates who can tell compelling stories with data, your projects in this programme will give you opportunities to combine different presentation methods.
Using research from the Leeds Institute of Data Analytics, and others, you’ll work on projects in innovative areas such as AI, health informatics, urban analytics, statistical and mathematical methods, and visualisation and immersive technologies. Experience in these areas will help you prepare for the future of data science.
As a graduate of this programme, you'll be able to:
- Illustrate a comprehensive understanding of key statistical methods and their practical application.
- Demonstrate thorough knowledge in various specialised topics within statistics such as Bayesian modelling, Monte Carlo estimation and dimension reduction.
- Select and apply tools and techniques for using statistical methods in context.
- Acquire transferable skills and the ability to work independently through the completion of a practical data analysis project.
- Build proficiency in key programming languages and techniques for data analysis.
- Develop effective analysis strategies for traditional “simple random sample” and “big data” (population) datasets differ.
- Analyse large datasets (including ones with more variables than observations).
- Describe issues of data ethics and governance, as well as evaluate the impact of these issues on data gathering and analysis.
This online degree is offered on Coursera. The next cohort starts on 3 March 2025.
Master Data Science Online: Webinar with University of Leeds Experts
Discover what makes the University of Leeds' online MSc Data Science (Statistics) exceptional. Join our webinar to learn about our top features, application tips, and how to advance your career in data science or statistics.
Join our online taster courses
Our short online courses on Coursera will familiarise you with topics explored on the online master's.
- Understand the basics of programming used in Data Science and introduce you to the Python programming language. Sign up for Programming for Data Science on Coursera.
- Learn how to analyse and investigate data sets and explore creative ways to visualise data with Exploratory Data Analysis on Coursera
- Enhance your statistics and probability skills by exploring the difference between data and information through real-life examples and practical software training. Sign up for Statistical Methods on Coursera.
Inside the Programme: Faculty Q&A Session
Course details
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
The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.
Year 1 compulsory modules
| Module Name | Credits |
|---|---|
| Programming for Data Science | 15 |
| Statistical Methods | 15 |
| Exploratory Data Analysis | 15 |
Year 1 optional modules (selection of typical options shown below)
| Module Name | Credits |
|---|---|
| Machine Learning | 15 |
| Linear Modelling | 15 |
| Project Skills | 15 |
| Statistical Learning | 15 |
| Data Science | 15 |
| Multivariate Methods | 15 |
Year 2 compulsory modules
| Module Name | Credits |
|---|---|
| Statistical Computing | 15 |
| Bayesian Statistics | 15 |
| Project | 15 |
Year 2 optional modules (selection of typical options shown below)
| Module Name | Credits |
|---|---|
| Machine Learning | 15 |
| Linear Modelling | 15 |
| Project Skills | 15 |
| Statistical Learning | 15 |
| Data Science | 15 |
| Multivariate Methods | 15 |
Learning and teaching
A global learning network
This comprehensive distance learning masters degree is delivered 100% online through the Coursera platform. 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 learninglearn 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.
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.
Applying
Entry requirements
Route 1: Standard Entry
To meet the standard entry requirements, you need a 2:1 Bachelor of Science honours degree (3.0 GPA). Transcripts should show evidence of at least 5 undergraduate modules in a combination of mathematics and statistics. At least one module should be in Statistics, and all modules should be across at least 2 years of your previous study.
Route 2: Performance Pathway
To qualify for the performance pathway entry route, you need to meet one of the following criteria:
- a minimum of a third-class Bachelor of Science honours degree (2.2 GPA) or a minimum of a third-class Bachelor of Engineering degree (2.2 GPA), or
at least 3 years of relevant professional experience. This experience should demonstrate competencies in:
Working with large data sets
Visualising and summarising data
“Cleaning” data
Data modelling
Statistical analysis
Using statistical software such as R, SPSS, or Python
We will send you an additional document to complete as part of the next steps.
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. Alternatively, you can see more information on the Coursera platform on the link below.
Read our how-to-apply guidance before you start your application.
This online degree is offered through the Coursera platform.
Application deadline: 28 January 2025.
Admissions policy
University of Leeds Admissions Policy 2025
Contact us
Online Admissions team
Email: onlineadmissions@leeds.ac.uk
Telephone:
Fees
UK: £15,000 (Total)
International: £15,000 (Total)
Fees for 2024/25 academic year of entry (1 September 2024 to 31 August 2025):
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
Graduates of the University of Leeds (or an affiliated institution) are entitled to a 10% bursary towards tuition fees. Find out more about eligibility and how to apply.
UK students may be able to apply for a UK government-backed loan. Applications should be made through the Student Loans Company. 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.
Careers support
You will have access to our Careers Service that offers extensive online resources including career planning, advice on CV writing, job applications and key interview skills.