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Students
Tuition Fee
GBP 18,250
Per year
Start Date
2026-09-01
Medium of studying
On campus
Duration
1 years
Program Facts
Program Details
Degree
Masters
Major
Artificial Intelligence | Data Analytics | Data Science
Area of study
Information and Communication Technologies
Education type
On campus
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
GBP 18,250
Intakes
Program start dateApplication deadline
2026-09-01-
About Program

Program Overview


MSc Data Science

About this course

Study 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.


  • 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

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 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.


MSc Data Science is available for study as either a 180 credit or 240 credit routeway.


The 180 credit version of the course is usually run over one full year with the taught modules in Semesters 1 and 2, and the independent research project in the summer. The 240 credit routeway is studied over two years: Semesters 1 and 2 in both years.


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:


  • consolidate knowledge and skills learned during the first year, as well as develop new ones
  • provide an opportunity to further use the tools and systems that data scientists and data engineers use, increasing your readiness for the job market
  • equip you with the transferrable project management skills needed to excel in your chosen career

Course modules

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.
  • Machine Learning and 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.
  • Efficient algorithms for complex data sets (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.

Optional modules

  • Work Based Project (60 credits)
    • The Work Based Project aims to apply data science to the solution of a real-world problem, which will help to consolidate knowledge and skills learnt using the tools and systems that data scientists and data engineers use.

Your Learning Experience

  • Teaching: Acquisition of knowledge through lectures, seminars, practicals, directed reading, focused literature review exercises, coursework assignments, student discussion groups and tutorials.
  • Assessment: Testing of the knowledge base is through a combination of continuous assessment methods, short and extended computer based assignments, formal written examinations, project report or dissertation, and oral presentations.

Career paths

  • Further your career prospects
  • LJMU has an excellent employability record with 94% (HESA 2022) of our postgraduates in work or further study fifteen 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 focused on preparing you for a career in industry or for PhD level study.

Tuition fees and funding

  • Home: £10,250
  • International: £18,250 (Year 1), £5,870 (Year 2)
  • Scholarships: LJMU provides a variety of postgraduate scholarships to support international students.

Entry requirements

  • Home: a minimum 2:2 in a numerate, scientific or computer-based subject; an A level, or equivalent, in Mathematics at Grade C or more
  • International: IELTS 6.5 (minimum 6.0 in each component)

How to apply

  • To apply for this programme, you are required to complete an LJMU online application form.
  • You will need to provide details of previous qualifications and a personal statement outlining why you wish to study this programme.
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