Big data is becoming more and more important in fields from science to marketing, engineering medicine and government. This programme 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 systems programming and algorithms, 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, or broaden your approach with topics like cloud computing.
As one of the few schools with expertise covering text, symbolic and scientific/numerical data analysis, we can provide a breadth of expertise to equip you with a variety of skills – and you’ll work as an integral member of one of our research groups when you develop your main project. We also have close links with the Leeds Institute for Data Analytics which is at the forefront of big data research.
You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.
We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.
Core modules in Semester 1 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.
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.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 will study.
These are typical modules/components studied and may change from time to time. Read more in our Terms and conditions.
- Machine Learning 10 credits
- Big Data Systems 15 credits
- Data Science 15 credits
- MSc Project 60 credits
- Information Visualization 10 credits
- User Adaptive Intelligent Systems 10 credits
- Distributed Systems 10 credits
- Combinatorial Optimisation 10 credits
- Secure Computing 10 credits
- Graph Algorithms and Complexity Theory 10 credits
- Bio-Inspired Computing 15 credits
- Knowledge Representation and Reasoning 15 credits
- Algorithms 15 credits
- Parallel and Concurrent Programming 15 credits
- Cloud Computing 15 credits
- Semantic Technologies and Applications 15 credits
- Image Analysis 15 credits
- Scheduling 15 credits
- Scientific Computation 15 credits
- Graph Theory: Structure and Algorithms 15 credits
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 be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.
Entry requirements, fees and applying
A bachelor degree with a 2:1 (hons) in computing or a related subject with a substantial computing element. Relevant work experience will also be considered.
We expect you to have programming competence, some prior experience of systems development and knowledge of data structures and algorithms.
All applicants will need to have GCSE English Language at grade C or above, or an appropriate English language qualification.
We accept a range of international equivalent qualifications.
English language requirementsIELTS 6.5 overall, with no less than 6.0 in any component.. For other English qualifications, read English language equivalent qualifications.
Improve your English
If English is not your first language, you may be able to take a pre-sessional course before you begin your studies. This can help if you:
- don't meet the English language requirements for your course or
- want to improve your understanding of academic language and practices in your area of study.
Our pre-sessional courses are designed with a progression route to the degree programme and are tailored to the subject area. For information and entry requirements, read Language for Science and Engineering B (6 weeks) and Language for Science and Engineering A (10 weeks).
How to apply
International: 31 July 2017
UK/EU: 10 September 2017
Applicants are encouraged to apply as early as possible. Any applications submitted after this deadline may be considered on a case by case basis.
This link 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.
UK/EU: £10,000 (total)
International: £19,500 (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
The School of Computing offer a range of scholarships for UK, EU and International students. Find out more about our Scholarships.
Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used 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 gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, 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.
Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.
You’ll have access to the wide range of engineering and computing careers resources held by our Employability team in our dedicated Employability Suite. You’ll have the chance to attend industry presentations book appointments with qualified careers consultants and take part in employability workshops. Our annual Engineering and Computing Careers Fairs provide further opportunities to explore your career options with some of the UKs leading employers.
The University's Careers Centre also provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.
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 MSc Advanced Computer Science 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.