Advanced Computer Science (Data Analytics) MSc

Year of entry

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Start date
September 2024
Delivery type
On campus
Duration
12 months full time
Entry requirements
A bachelor degree with a First (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
£13,500 (Total)
International fees
£31,750 (Total)

Course overview

Student at a laptop

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:

  • Research produced by the Leeds Institute for Data Analytics and our School’s globally-renowned research conducted right here on campus feeds directly into the course, shaping your learning with the latest thinking.
  • Benefit from studying at a university that’s partnered with 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.
  • Gain a breadth of expertise in areas like text, symbolic and scientific/numerical data analysis, alongside having 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 cloud computing, machine learning, deep learning, algorithms and data mining.
  • Build industry experience by conducting 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.
  • Study in the Sir William Henry Bragg building which provides excellent facilities and teaching spaces for an outstanding student experience.

Course details

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.

Project work

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.

Course structure

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

Module Name Credits
Data Science 15
Cloud Computing Systems 15
MSc Project 60
Machine Learning & Knowledge Representation and Reasoning 15

Year 1 optional modules (selection of typical options shown below)

Module Name Credits
Blockchain Technologies 15
Knowledge Representation and Reasoning 15
Deep Learning 15
Algorithms 15
Programming for Data Science 15
Data Mining and Text Analytics 15
Advanced Software Engineering 15
Scientific Computation 15
Graph Theory: Structure and Algorithms 15

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.

Specialist facilities

At Leeds, we provide an exciting environment in which to gain a range of skills and experience cutting-edge technology.

You’ll benefit from world-class facilities to support your learning, including:

  • A state-of-the art computing cluster, equipped with Azure services and a visualisation lab including a Powerwall, benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker
  • Individual machines, equipped with Microsoft or Linux software, capable of performing rendering
  • Robotics labs
  • Dedicated Linux laboratories with a combined capacity of an average of 150 machines
  • Excellent facilities and teaching spaces in the Sir William Henry Bragg building.

Programme team

Programme leader, Dr Mark Walkley, specialises 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.

Assessment

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.

Applying

Entry requirements

A bachelor degree with a First (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. Find out more about our six week online pre-sessional.

You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.

How to apply

Application deadlines

We operate a staged admissions process for this course with selection deadlines throughout the year.

Please read our How to Apply page for full details, including application deadlines and what to include with your application.

Click below to access the University’s online application system and find out more about the application process.

If you're still 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.

Admissions policy

University of Leeds Taught Admissions Policy 2024

This course is taught by

School of Computing

Contact us

Postgraduate Admissions team

Email: pgcomp@leeds.ac.uk
Telephone:

Fees

UK: £13,500 (Total)

International: £31,750 (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 on our living costs and budgeting page.

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.

Career opportunities

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 5 most targeted universities in the UK by graduate recruiters, according to High Fliers’ The Graduate Market in 2024 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

Careers support

At Leeds, we help you to prepare for your future from day one. We have a wide range of careers resources — including our award-winning Employability team who are in contact with many employers around the country and advertise placements and jobs. They are also on hand to provide 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, write your CV and cover letter, 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.

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