Data Science (Statistics) MSc

Year of entry

Register your interest

This online degree is offered through the Coursera platform. Find out more

Start dates
September 2024
March 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
See fees section below
International fees
See fees section below

Course overview

Students chatting around a table

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 through the Coursera platform. The next cohort starts on 9 September 2024.

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.
  • Learn how to analyse and investigate data sets and explore creative ways to visualise data with Exploratory Data Analysis.

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.

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

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 a minimum of a third-class Bachelor of Science honours degree and you’ll also need to achieve a pass (50% weighted average or higher) in both of the first two degree modules to remain on the degree: Programming for Data Science and Statistical Methods. You do not need to complete these modules before you enrol, they will simply form part of your first term studying the degree. 

If you do not achieve a pass (50% weighted average or higher) in both of the first two modules, you will not be able to continue and will be withdrawn from the degree.

Should this be the case and you have progressed onto the third module of the degree before the results of the second module are known then you will be refunded for the cost of the third module.  

All applicants will need to have GCSE English language at grade C or above, or an appropriate equivalent English language qualification.

We accept a range of international equivalent qualifications. For information, please 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

This online degree is offered through the Coursera platform.

Application deadline: 30 July 2024

Admissions policy

University of Leeds Taught Admissions Policy 2024

Contact us

Online Admissions team

Email: onlineadmissions@leeds.ac.uk
Telephone:

Fees

UK: See fees section below

International: See fees section below

Fees for 2023/24 academic year of entry (1 September 2023 to 31 August 2024):

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

There is a limited time promotion for applicants who are self-funding: Apply before 5 November 2023 and if accepted and you subsequently enrol in the January 2024 cohort of the MSc Data Science (Statistics), you will get one module worth £1,250 for FREE. See more details.

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.