Advanced Computer Science (Data Analytics) MSc

Course overview

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 Computer Science 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 data science, cloud computing and machine learning.
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 deep learning, knowledge representation, blockchain technologies, data mining and text analytics.

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.

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

Compulsory modules

Data Science – 15 credits

The aim of the module is for you to understand methods of analysis that allow people to gain insights from complex data. You’ll cover the theoretical basis of a variety of approaches, placed into a practical context using different application domains.

Cloud Computing Systems – 15 credits

The module aims to develop a practical understanding of methods, techniques and architectures needed to build big data systems, so that knowledge can be extracted from large, diverse data sets. This module is supported by the strong research interest and expertise in cloud and related technologies within the School of Computer Science. You’ll develop expertise in cloud computing and big data systems as you’re taught the skills and knowledge to design, build and extend the Internet infrastructure and to design a variety of applications.

Machine learning - 15 credits

This module covers topics selected from: Decision trees, Bayesian networks, instance-based learning, kernel machines, clustering, reinforcement learning inductive logic programming, artificial neural networks, deep learning.

MSc Project – 60 credits

You’ll undertake a research project during the summer months. 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 include:

• Text mining of e-health patient records
• Java-based visualisation on ultra-high resolution displays
• Data mining of sports performance data.

A proportion of projects are formally linked to industry and can include spending time at the collaborator’s site over the summer.

Optional modules

Please note: The modules listed below are indicative of typical options.

Blockchain Technologies – 15 credits

This module provides a comprehensive knowledge on fundamentals and practical aspects of distributed ledgers and their applications in society. Starting from required knowledge on distributed systems and security, this module moves to the “big picture” of the different blockchain architectures that have been evolving in this dynamic technological landscape.

Knowledge Representation and Reasoning – 15 credits

You’ll analyse descriptions of complex real-world scenarios in terms of formal representation languages and, on completion, understand automated reasoning and ontology as well as their applications.

Deep Learning – 15 credits

The module introduces the field of Deep Learning, taking a strongly integrative and state of the art approach. You will gain hands-on experience in developing systems to address real-world problems, providing the knowledge and skills necessary to develop an AI system as part of an MSc project.

Algorithms – 15 credits

Algorithms and algorithmic problem solving are at the heart of computer science. This module introduces the design and analysis of efficient algorithms and data structures. You'll learn how to quantify the efficiency of an algorithm and what algorithmic solutions are efficient. You’ll also be taught techniques for designing efficient algorithms, including efficient data structures, standard methods such as Divide-and-Conquer and Dynamic Programming as well as more advanced techniques. This is done using illustrative and fundamental problems relevant to AI.

Programming for Data Science – 15 credits

This module is designed to give those with little or no programming experience a firm foundation in programming for data analysis and AI systems. The module will also fully stretch those with substantial prior programming experience (e.g. computer scientists) to extend their programming and system-building knowledge through self-learning supported by online courseware.

Data Mining and Text Analytics – 15 credits

Introduction to linguistic theory and terminology. Understand and use algorithms and resources for implementing and evaluating text mining and analytics systems. Develop solutions using open-source and commercial toolkits. Consider the applications of data mining and text analytics through case studies in information retrieval and extraction.

Advanced Software Engineering – 15 credits

In this module, you’ll build on prior knowledge of software engineering principles, expanding it to include a more thorough understanding of what constitutes good design. You’ll learn how design can be improved using patterns and refactoring, and you’ll gain a broad appreciation of the different architectural styles used in modern software.

Scientific Computation – 15 credits

This module will support your understanding of the range of problems that can be formulated as nonlinear equation systems. On completion, you should be able to: consider standard algorithms for these problems and the efficiency of their implementation; and demonstrate how state-of-the-art algorithms deliver gains in efficiency and allow the solution of large, sparse systems of nonlinear equations.

Graph Theory: Structure and Algorithms – 15 credits

Graphs are an extremely powerful tool for modelling real-world systems, with applications in logistics, telecommunication, molecular biology, industrial engineering, linguistics, chemistry, and many other areas. Many of the optimisation problems arising from these applications are computationally difficult when there are no restrictions on the input. However, the scenarios that we aim to model often impose additional conditions on the structure of the corresponding graphs. This module focuses on how that structural information can be used to solve the relevant optimisation problems efficiently, with an emphasis on mathematical precision.

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 UK-leading facilities to support your learning, including:

• A state-of-the art computing cluster, with access to Azure services and GPU computing as required by your modules 
• High-performance graphics workstations, equipped with modern software libraries and tools for virtual reality and real time visualisation and interaction
• 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

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 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.

Applicants with any of the following will be considered on a case-by-case basis:

• A bachelor degree with a 2:1 (hons) in other computing-based degrees.
• Professional qualifications and relevant work experience.

International

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

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

Applicants are encouraged to apply as early as possible.

30 June 2025 – International applicants

12 September 2025 – UK applicants

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 Admissions Policy 2025

This course is taught by

School of Computer Science

Contact us

Postgraduate Admissions team

Email: pgcomp@leeds.ac.uk
Telephone:

Fees

UK: £14,250 (Total)

International: £33,750 (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.

Explore more about your employability opportunities at the University of Leeds.

Find out more about career support.