Advanced Computer Science (Data Analytics) MSc
Year of entry 2023
- Start date
- September 2023
- Delivery type
- On campus
- 12 months full time
- Entry requirements
- A bachelor degree with a 2:1 (hons) in computer science. We require all applicants to have studied a breadth of relevant modules including significant programming, systems development, data structures and algorithms, with strong marks across all these modules.
Full entry requirements
- English language requirements
- IELTS 6.5 overall, with no less than 6.0 in any component
- UK fees
- £12,750 (total)
- International fees
- £28,000 (total)
From science to marketing, engineering to medicine, big data has become crucial to a wide range of industries – especially in recent years. That’s why many organisations are keen to employ qualified experts in computing who have a particular focus in data to keep their businesses progressing.
Our Advanced Computer Science (Data Analytics) MSc will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science.
You’ll gain a foundation in topics like data science, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like image analysis or text analytics with the chance to broaden your approach with topics like cloud computing.
Studying in our School of Computing gives you access to a whole range of specialist facilities, whilst being taught by academics who are experts in their fields. We’re responsible for producing internationally excellent research and have long-established links in industry and with the Leeds Institute for Data Analytics (LIDA) which is at the forefront of big data research.
Once you’ve graduated, you’ll be fully equipped with the most up-to-date practices and techniques, alongside the technical skill set you’ll need to pursue an exciting career in industry.
Why study at Leeds:
- Learn the latest innovations in computer science from research produced by the Leeds Institute for Data Analytics and our School’s world-leading research conducted right here on campus that feeds directly into the course.
- Benefit from studying at a university that is a partner of the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.
- Advance your knowledge and skills in key areas of computing including data science and machine learning.
- You’ll gain breadth of expertise in areas like text, symbolic and scientific/numerical data analysis, whilst giving you the opportunity to work as an integral member of one of our research groups when you develop your main project.
- Tailor the degree to suit your specific interests with a selection of optional modules to choose from such as advanced software engineering, artificial intelligence, algorithms and data mining.
- Build industry experience and conduct your own individual project which focuses on a real-world topic of your choice, giving you the chance to develop professional skills in research and critical thinking.
- Access a wide range of industry-standard specialist facilities including a state-of-the-art cloud computing lab, a large High Performance Computing (HPC) resource and a robotics lab with a range of equipment available for specialist MSc projects.
- Experience expert theoretical and practical teaching delivered by a programme team made up of academics who specialise in a wide range of computing topics.
- Enhance your career prospects and join our successful alumni who have secured jobs in many excellent organisations worldwide.
- Study in the Sir William Henry Bragg building, a brand-new development providing excellent facilities and teaching spaces for an outstanding student experience.
- Make the most of your time at Leeds by joining CompSoc, where you can meet like-minded undergraduate and postgraduate students in the School of Computing through fortnightly events covering a range of activities including socials, sports and Hackathons!
In the first half of the year, you'll study core modules which will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming, as well as the basic principles of automated reasoning, machine learning and how computers can be made to represent knowledge.
From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, cloud computing, semantic technologies and developing mobile apps.
In the second half of the year, over the summer months, you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.
The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.
Recent projects for Advanced Computer Science (Data Analytics) MSc students have included:
- Text mining of e-health patient records
- Java-based visualization on ultra-high resolution displays
- Data mining of sports performance data
- Contour topology
- Efficient computation for simulating tumour growths
A proportion of projects are formally linked to industry and can include spending time at the collaborator’s site over the summer.
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 Advanced Computer Science (Data Analytics) MSc in the course catalogue
Year 1 compulsory modules
Year 1 optional modules (selection of typical options shown below)
|Knowledge Representation and Reasoning||15|
|Programming for Data Science||15|
|Data Mining and Text Analytics||15|
|Advanced Software Engineering||15|
|Graph Theory: Structure and Algorithms||15|
Want to find out more about your modules?
Take a look at the Advanced Computer Science (Data Analytics) module descriptions for more detail on what you'll study.
Learning and teaching
Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.
Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.
You’ll benefit from world-class facilities to support your learning, including:
- a state-of the art cloud computing lab with a 10-node cluster
- a large High Performance Computing (HPC) resource consisting of several clusters which are used for all forms of predictive modelling, data analysis and simulation
- a visualisation lab including a Powerwall, benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker
- Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices
- Twin Immersion Corp CyberGloves
- rendering cluster and labs containing both Microsoft and Linux platforms, among others.
- You'll study in the Sir William Henry Bragg building, a brand-new development providing excellent facilities and teaching spaces for an outstanding student experience.
It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.
Our Virtual Learning Environment will help to support your studies: it’s a central place where you can find all the information and resources for the School, your programme and modules.
You can also benefit from support to develop your academic skills, within the curriculum and through online resources, workshops, one-to-one appointments and drop-in sessions.
Programme leader, Dr Mark Walkley, specialise in Scientific Computing and the use of parallel computing to enable large-scale, accurate simulations of physical systems from a range of other academic disciplines. His areas of teaching range from introductory programming to computer networks and parallel computing.
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.
You’ll be assessed using a range of techniques which may include case studies, technical reports, group work, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.
A bachelor degree with a 2:1 (hons) in computer science. Other Computing based degrees may be considered on a case by case basis.
We require all applicants to have studied a breadth of relevant modules including significant programming, systems development, data structures and algorithms, with strong marks across all these modules.
Relevant work experience will also be considered.
We accept a range of international equivalent qualifications. For more information please contact the Admissions Team.
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.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Engineering (6 weeks) and Language for Science: Engineering (10 weeks).
We also offer online pre-sessionals alongside our on-campus pre-sessionals. You could study a part-time online course starting in January, or a full-time course in summer. Find out more about online pre-sessionals.
You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.
How to apply
We operate a staged admissions process for this course with selection deadlines throughout the year.
Please read our Staged Admissions page for full details, including application deadlines and what to include with your application.
The ‘Apply’ link at the top of this page takes you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.
Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.
University of Leeds Taught Admissions Policy 2023
This course is taught by
Postgraduate Admissions team
UK: £12,750 (total)
International: £28,000 (total)
Read more about paying fees and charges.
For fees information for international taught postgraduate students, read Masters fees.
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 about additional costs.
Scholarships and financial support
If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government. Find out more at Masters funding overview.
Computing is an essential component of nearly every daily activity, from the collection and processing of information in business, through to smart systems embedded in devices, image processing in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.
This programme will give you the practical skills to enter many areas of applied computing, working as application developers, system designers and evaluators. Links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well-prepared for a range of careers, as well as further research at PhD level.
Plus, the University of Leeds is in the top five most targeted universities in the UK by graduate recruiters, according to High Fliers’ The Graduate Market in 2022 report.
Here’s an insight into some of the job positions and organisations previous advanced computer science graduates have secured:
- Engineer, Johns Hopkins University Applied Physics Laboratory
- Senior Software Engineer, Funding Circle
- Technical Developer, Reading Room
- Head of Audience Development, Al Jazeera Media Network
- Systems Engineer, Systematic
- Software Engineer, THG
- Programmer, Alibaba
- PhD candidate, Monash University
At Leeds, we help you to prepare for your future from day one. Our wide range of careers resources — including our award-winning Employability team — are on hand to offer guidance and support, ensuring you are prepared to take your next steps after graduation and get you where you want to be.
- Employability events — we run a full range of events including careers fairs in specialist areas and across broader industries — all with employers who are actively recruiting for roles.
- MyCareer system — on your course and after you graduate you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.
- Qualified careers consultants — gain guidance, support and information to help you choose a career path. You’ll have access to 1-2-1 meetings and events to learn how to find employers to target, research before interviews and brush up on your interview skills.
- Opportunities at Leeds — there are plenty of exciting opportunities offered by our Leeds University Union, including volunteering and over 300 clubs and societies to get involved in.
Find out more about career support.
Rankings and awards
Student profile: Saile Villegas
The taught modules such as Machine Learning, Big Data Systems and Data Science, amongst others, were very appealing before enrolling and I can assure you that they did not disappoint.Find out more about Saile Villegas's time at Leeds