Course Overview

Do you want to develop skills in the emerging discipline of data science?

Our unique Masters has been developed in conjunction with industry partners and offers you the opportunity to gain relevant skills and study specialist pathways to suit your interests. We bring together expertise from our School of Computing and Communications, Department of Mathematics and Statistics, Lancaster Environment Centre, Lancaster University Management School and CHICAS in the Faculty of Health and Medicine.

We offer a core set of data science modules with specialism in either computing or statistical inference, and a range of optional modules with themed pathways.

Students study core topics (75 credits) including:

  • research methodology
  • computer programming
  • data sourcing and management
  • statistical modelling and inference
  • the use of computing technology to handle large and complex data sets

A variety of routes through the MSc are then available. You can choose from a range of elective modules (45 credits) according to your skills, interests and career aspirations. These modules are grouped into the following themes:

  • Societal
  • Population Health
  • Environmental
  • Bioinformatics
  • Business Intelligence
  • Computing

You will then undertake a 12-week summer placement either within an industry in a business setting, or as part of an academic research project (dissertation 60 credits).  This course will prepare you for a direct entry into careers as data scientists or for research leading to a PhD. The MSc course is designed to be studied full-time over one year, but part-time study over two years is possible.

If you would like to apply for one of our Data Science Masters degrees, you need to use Lancaster University's My Applications website.

Who can Apply?

We expect to recruit students who are interested in a career at the interface of computing, statistics and their application.

For the MSc in Data Science you should hold, or expect to obtain, a BSc in Mathematics, Statistics or Computing. People with a degree in related subjects such as Physics, Finance or Engineering may apply if you have A-Level Mathematics.

For applicants whose first language is not English, a recognised English qualification is required:

  • IELTS: 6.5 (with at least 6.0 in each skill)

Overseas students will require a visa to be able to study with us in the UK.

Fees and Funding

Fees are as follows:

  • UK and EU students: £8,500 (GBP)
  • Non-EU students: £19,500 (GBP)

For October 2018 intake, we have a small number of fee waiver scholarships meaning fees would be reduced to the following levels:

  • UK and EU students: £5,500 (GBP)
  • Non-EU students: £14,500 (GBP)

Smaller awards may be made, depending on the availability of funds. All eligible applicants will be automatically considered and those successful will be notified via email. There is no separate application process for these scholarships. Scholarships will be awarded on a rolling basis whilst funds are available.

Lancaster University offers postgraduates a range of scholarships. See here for more details.

How to Apply

If you would like to apply for one of our Data Science Masters degrees, you need to use Lancaster University's My Applications website.

Supporting documentation includes:

  • Your degree transcripts and certificates, including certified English translations if applicable
  • Two references
  • If English is not your first language, you should also enclose copies of any English language test results

You also need to complete a personal statement to help us understand why you wish to study your chosen degree. MSc Data Science applications should include a statement regarding your intended specialism: Computing or Statistical Inference.

If you are a current Lancaster University student, you will not need to provide your Lancaster degree transcript and only need to provide one reference.

If you would like to apply for one of our Data Science Masters degrees, you need to use Lancaster University's My Applications website.

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Student Profiles

Haiqin Zhuang

Former MSc Data Science student Haiqin Zhuang from China gives her views on the course and life at Lancaster University.

What did you do before coming here?

I’m originally from Fujian in eastern China. I did my A-levels in London and then a Pure Maths degree at Lancaster University.

Why did you decide to apply for this course?

I believed that the course would allow me to develop computing skills to add to the mathematical skills I developed during my first degree. I saw that being able to demonstrate skills in both areas would give me a good chance of securing an interesting and well-rewarded job.

Why did you choose this course rather than others?

I wanted a course that would allow me to gain experience in the technologies used in commercial data science that would enable me to apply my mathematical knowledge and would enable me to gain work experience through an industry placement.

What will you do after the MSc?

I am looking for a role as a commercial data scientist with a view towards progressing to a managerial role in data analytics.

What are the best things about this course?

Being on this course has developed my confidence in a number of areas – in programming, data mining, visualisation and in the presentation of my results. The modular format of the course allowed me to shape my own learning in the areas most appealing to me. The industry placement made the course very attractive as this is a way to leave University with proof that I’m able to use data science techniques in the workplace. I have also been pleased with the diverse nature of the students on this course – being able to share ideas with people from different countries and different backgrounds has really helped us to learn.

What placement will you be performing?

I will be spending 3 months with The Co-operative Insurance company in Manchester. I will be working on developing and testing models within their analytics team and will be able to see the results of my work applied to their business.

What do you hope to get from the placement?

I’m hoping to gain familiarity with how data science is used within a commercial organisation and what can be achieved using analytics. I’m looking to enhance my skills in SAS and SQL and, hopefully, be well-placed to find a good job in data science afterwards.

Sam Johnson

Former MSc Data Science student Sam Johnson gives his views on the course and life at Lancaster University.

What did you do before coming here?

I’m originally from Preston and have lived in this region all my life. I ran my own company specialising in IT sales and support for small to medium enterprises for several years.

Why did you decide to come on this course?

I saw a downturn in sales and repairs as more companies moved from having their own IT infrastructure to making use of remote services. I realised that the future value of IT systems was in data rather than hardware and saw this MSc as being a way of building my skills in this area. I also saw the course as providing me with the skills necessary to build a career in cloud-based computing.

Why did you choose this course rather than others?

Lancaster University has an excellent reputation for teaching and research and I believed that obtaining an MSc from the University would greatly enhance my CV. The Data Science MSc appealed to me as it gives access to a range of cutting-edge technical skills and also provides access to the mathematical skills necessary to draw reliable conclusions from data. I was also impressed by the inclusion of opportunities to develop soft skills and the inclusion of an industry data science placement.

What will you do after the MSc?

I am considering a PhD in the application of Data Science to Cybersecurity or perhaps an industry role in this area.

What are the best things about this course?

I’ve found the course to be very well managed and run and it covers very interesting material. I’ve enjoyed the practical aspects of the course, particularly the opportunity to perform data mining on real-world data sets and report conclusions back to sponsoring companies.

What placement will you be performing?

I will be spending 3 months with Fujitsu’s Security Computing Centre working on the analysis of cybersecurity data. The project aims at enhancing the early detection of cyber attacks through the rapid analysis and correlation of multiple data sources.

What do you hope to get from the placement?

I’m hoping for the opportunity to use the skills that I have developed in the course in a real-world environment and to developing a data science solution that provides real value. I’m looking forward to working with a commercial project team, learning from trained professionals and, hopefully, gaining the opportunity for further work with Fujitsu after the placement concludes.

Philip Spanoudes

Former Data Science MSc student Philip Spanoudes from Cyprus gives his views on the course and life at Lancaster University.

What did you do before coming here?

I’m originally from Cyprus. I came to the UK to take a BSc at Portsmouth University. I worked for a year as a software developer for NCR.

Why did you decide to come on this course?

I became interested in building a career as a data scientist and worked as a junior data scientist on a project for Flight Data Services Ltd. This project aimed at deriving insight from aircraft and travel information. I worked with a Statistics PhD student and was able to gain an appreciation of the value of statistical techniques for the extraction of meaning from data. I believed that I had strong coding and computer science skills, but felt that I would need further understanding of statistics if I was to progress as a data scientist. I chose Lancaster’s course rather than others as I felt that there was a stronger emphasis on statistical theory and that I would be able to learn a wider range of techniques.

I was also interested in the opportunity to use the skills taught in the course by taking an industry placement and also being able to learn how to produce effective data visualisations.

Why did you choose this course rather than others?

I wanted a course that would allow me to gain experience in the technologies used in commercial data science, that would enable me to apply my mathematical knowledge and would enable me to gain work experience through an industry placement.

What will you do after the MSc?

I am looking to develop new techniques in machine learning that will enable me to investigate setting up my own enterprise in offering data science as a service.

What are the best things about this course?

I’ve enjoyed the wide range of topics that are available on the course and that students are able to choose the areas on which they want to focus. The availability of funded industry placements with prestigious companies is also great.

What placement will you be performing?

I will be working with Framed Data Inc. investigating the application of deep learning techniques to their analysis of churn prediction. Churn prediction allows a company to determine which of their customers are likely to leave and take steps to prevent this – my project is aimed at finding efficient and effective ways of enhancing this process. I’ll spend most of my time in Lancaster, but will be going to work with Framed Data in San Francisco for a couple of weeks during the Summer. I’m really excited to have the opportunity to work with cutting-edge data science with Silicon Valley.

What do you hope to get from the placement?

I’m looking to develop my understanding of deep learning, to deliver real innovation to Framed Data and to enhance both my skills and CV with a great project.