MSc Data Science

Start date(s)

September 2021

Study mode

Full-time (1 year)

Full-time (2 years)

Tuition fees 21/22

Home (full-time, per year): £8,500

International (full-time, per year): £16,100

Year 2: £5,366

Faculty of Engineering and Technology:

0151 231 2777

International enquiries

Send a message >

About this course

This programme is also available as a 240 credit routeway studied over two years. Students who choose this option will undertake a group design project and dissertation.

  • Study a ground-breaking curriculum linked to industry needs 
  • Use industry standard tools and methodologies    
  • Undertake an extended project using real world data science problems
  • Learn from academics who are world-leading researchers
  • Use the programme as a basis for PhD study

Data Science is an emerging discipline that aims to extract unique insights by extending the field of statistics to incorporate advances in computing, particularly in relation to large quantities of data.

It is estimated that 90% of the world's data was created in the last two years and that each day, over 2.5 billion gigabytes of data is created. Between 2012 and 2017 the take up of big data analytics amongst large enterprises in the UK more than doubled from 14% to 29%. The number of big data specialist staff working in large firms is predicted to increase by 243% to approximately 69,000 employees.

The challenges in data science are multi-faceted and very complex in their nature, including handling the huge amount of data in incompatible legacy databases.  By exploiting cloud computing services, data scientists are now relatively free from the constraints of hardware and can concentrate on applying their domain knowledge and experience to make sense of the data. They can apply advanced statistical techniques and machine learning algorithms to make informed decisions which can deliver a major impact on their organisations. The programme comprises six core modules covering statistical and computing techniques plus an extended research project. It is designed to give you the knowledge to move into the world of work as a qualified Data Scientist or to carry out further research through a PhD or equivalent. It is delivered via a combination of lectures, tutorials and and hands-on computer laboratory sessions. A major component of the MSc programme is the research project module, which will give you the opportunity to work on a high-level original research topic, with guidance from an experienced researcher and supervisor.


The new 240 credit route includes a Group Design Project which aims to apply data science to the solution of a real-world problem. This will help to consolidate knowledge and skills learned during the first year, as well as develop new ones.

Why should I choose the 2 year route?

  • The Group Design Project will provide an opportunity to use the tools and systems that data scientists and data engineers use, increasing your readiness for the job market. 
  • This route will equip you with the transferrable project management skills needed to excel in your chosen career.
  • You will work in groups and meet regularly with an academic supervisor and any internal or external stakeholders in order to develop an effective team-working ethic.
  • You will present your work through regular meetings with your supervisor as well as submitting progress reports and oral presentations. In this way you will have the chance to hone your communicative skills and leave University ready for the workplace.

    Data Science   

Fees and funding

There are many ways to fund postgraduate study for home and international students


The fees quoted at the top of this page cover registration, tuition, supervision, assessment and examinations as well as:

  • Library membership with access to printed, multimedia and digital resources
  • Access to programme-appropriate software
  • Library and student IT support
  • Free on-campus wifi via eduroam

Additional costs

Although not all of the following are compulsory/relevant, you should keep in mind the costs of:

  • accommodation and living expenditure
  • books (should you wish to have your own copies)
  • printing, photocopying and stationery
  • PC/laptop (should you prefer to purchase your own for independent study and online learning activities)
  • mobile phone/tablet (to access online services)
  • field trips (travel and activity costs)
  • placements (travel expenses and living costs)
  • student visas (international students only)

Image showing assortment of notes and coins.

  • study abroad opportunities (travel costs, accommodation, visas and immunisations)
  • academic conferences (travel costs)
  • professional-body membership
  • graduation (gown hire etc)


There are many ways to fund postgraduate study for home and international students. From loans to International Scholarships and subject-specific funding, you’ll find all of the information you need on our specialist postgraduate funding pages.

Please be aware that the UK’s departure from the EU may affect your tuition fees. Learn more about your fee status and which tuition fees are relevant to you.


Further your career prospects

LJMU has an excellent employability record with 96% (HESA 2018) of our postgraduates in work or further study six months after graduation. Our applied learning techniques and strong industry connections ensure our students are fully prepared for the workplace on graduation and understand how to apply their knowledge in a real world context.

This programme is particularly focussed on preparing you for a career in industry or for PhD level study.

​Data science is a growing area of demand with a predicted scarcity of expertise forecast over the next decade. LJMU has strong links with many graduate employers of data scientists who value the skills developed in the course such as accessing, manipulating and drawing insight from large volumes of complex data; assimilating information from the research literature and scientific and technical writing.

Image of Postgraduate

The programme enables you to plan and complete a substantial programme of original research at the highest level. We expect that many projects should have the potential to result in papers in refereed journals and serve as the starting point for PhD level work.

The student experience

Discover life as a postgraduate student at LJMU.

News and views

Browse through the latest stories and updates from the University and beyond

#LJMU invites businesses in the Liverpool City Region to #WorkwithLJMU as hosts for the Discovery Internship - Full…

Course modules

Discover the building blocks of your programme

Your programme is made up of a number of core modules which are part of the course framework. Some programmes also have optional modules that can be selected to enhance your learning in certain areas and many feature a dissertation, extended report or research project to demonstrate your advanced learning.

Image of students in classroom
Core modules

Introduction To Data Analytics
20 credits

This module aims to provide an introduction to the key concepts of data compilation, management, querying, cleaning and visualisation.

Statistical Methods In R
20 credits

This module provides an introduction to key concepts in statistics and statistical computing using the R programming language, with an emphasis on the informed interpretation of the results of statistical testing.

Big Data Computing
20 credits

This module aims to develop skills in modern computing techniques for high performance analysis of large data sets. It also provides an understanding of how to translate an analysis problem to best exploit such techniques.

Research Methods In Data Science
20 credits

This module aims to equip you with the research skills necessary to undertake your dissertation project. It covers the preparation of a research proposal or a business case (depending on the academic/industrial context), consideration of ethical and legal issues, literature review, oral and written presentation skills and project management.

Data Mining
20 credits

This module aims to develop skills in data mining, using methods from computational learning theory and artificial intelligence to extract previously unknown relationships from large data sets.

Big Data Analysis
20 credits

This module aims to develop skills in big data analysis, including techniques of dimensionality reduction and the application of statistical and machine learning models. In addition it aims to develop the key skill of working with experts from other domains.

Data Science Project
60 credits

This module allows you to display all of the skills learnt on the programme and give you the opportunity to demonstrate creativity, initiative, ingenuity and communication in an academic context.

Person sat using laptop


How learning is monitored on your programme

To cater for the wide-ranging content of our courses and the varied learning preferences of our students, we offer a range of assessment methods on each programme. Assessment techniques vary from module to module to reflect relevant assessment approaches and the key learning points of each topic.

You will be assessed via a combination of exams, coursework and an extended report based on your dissertation project. Typically 50% of your mark comes from coursework and 50% from an exam, although some modules may be assessed entirely by coursework done in the computer lab.

Course tutors

Our staff are committed to the highest standards of teaching and learning

Ivan Baldry

Prof Ivan Baldry

Featured tutors job title

Ivan joined Liverpool John Moores University in October 2005. His research is mainly in the area of galaxy properties, population statistics and evolution. This includes: measuring the galaxy stellar mass function, in particular to the lowest possible dwarf galaxy masses; how galaxies vary as a function of environment and how these relate to the forces shaping galaxy evolution; and measuring the properties of galaxy groups and how these relate to cosmological structure formation. Essential data are obtained from galaxy redshift surveys. The major ongoing survey that Ivan is working on is the Galaxy And Mass Assembly project. 

On graduation you may become a qualified Data Scientist or carry out further research at doctorate level.

School facilities

What you can expect from your School

The Astrophysics Research Institute in the Knowledge Quarter combines world-leading research in astrophysics with excellence in teaching at all levels. The Department of Applied Mathematics, based in the City Campus, is dedicated to producing research with real-world applications and offers a student-centered teaching portfolio. Teaching on this programme takes place in the city centre.

Order your brochure Research

Entry requirements

You will need:

  • a minimum 2:2 in a numerate, scientific or computer-based subject

  • an A level, or equivalent, in Mathematics at Grade C or more

Additional information:

  • RPL is not accepted on this programme

  • IELTS 6.5 (minimum 6.0 in each component)

If you have any specific queries, please contact

Image of student in library with book

Please note: All international qualifications are subject to a qualification equivalency check via NARIC.

View country specific entry requirements

Contact LJMU's International Admissions Team for guidance on visa information. Further information is also available from our international web pages.

Image of Students in classroom

Application and selection

Securing your place at LJMU

You will apply for the majority of postgraduate courses using our online application form. You should complete the form thoroughly and provide a detailed personal statement which reflects your suitability and aptitude for the programme.

The University reserves the right to withdraw or make alterations to a course and facilities if necessary; this may be because such changes are deemed to be beneficial to students, are minor in nature and unlikely to impact negatively upon students or become necessary due to circumstances beyond the control of the University. Where this does happen, the University operates a policy of consultation, advice and support to all enrolled students affected by the proposed change to their course or module.

Further information on the terms and conditions of any offer made, our admissions policy and the complaints and appeals process.

Important info about this course