Data Science (Statistics) MSc

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.

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 [email protected]

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.

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.