Gain hands-on experience of big data analytics, data mining and visualisation techniques using high-performance computer technology. This MSc is accredited by BCS, the Chartered Institute for IT, and includes an extended industrial placement in a real-world environment.
Introduction
Big data is increasingly important in the contemporary business and IT world. For many public and private enterprises, analysis of large-scale data sets is critical to growth. This MSc will prepare you for employment in an IT industry where big data professionals are in high demand.
You’ll learn how to interrogate vast amounts of data and make informed insights from datasets that are too large to be readily processed using standard techniques.
In year one, we’ll provide an overview of the key algorithms, algorithmic approaches and software environments you’ll use when solving big data problems and explore data mining techniques. We’ll also guide you in how to plan and conduct research.
Hands-on programming experience with the latest multi-core and multi-processor platforms will ensure your expertise in big data is underpinned by knowledge of high-performance computing. Further opportunities to specialise and enhance your knowledge of algorithms, optimisation and machine learning are available through a range of optional modules.
In year two, you’ll undertake an industrial project in a real-world environment as part of an extended placement opportunity. While on placement, you’ll develop transferable skills and gain insight into the operations, products, practices and culture of the placement provider.
What you'll learn
Theoretical and practical aspects of programming for the latest multi-core and multi-processor platforms
Key algorithms, approaches and software environments for developing solutions to big data problems
Data mining techniques and challenges using real-world datasets
Application of visualisation methods to data mining
Research skills in computer science
Bio-inspired algorithms for optimisation and machine learning
How to model continuous and discrete optimisation problems
The benefits and weaknesses of selected algorithmic techniques
Algorithmic aspects of game theory
Neural networks for artificial intelligence
How to validate systems against safety specifications
Accreditation
The programme is accredited by BCS, The Chartered Institute for IT, the leading professional body for those working in IT. It is continually updated to reflect new technologies and trends.
Discover what you'll learn, what you'll study, and how you'll be taught and assessed.
Year one
Compulsory modules
Research Methods in Computer Science (COMP516)
Credits: 15 /
Semester: semester 1
In this module the students will learn and practise all the necessary skills needed to conduct independent research in computer science, including literature search, project management, presentation techniques, peer reviewing, writing skills and critical review of texts. They will also learn about the professional, legal, social and ethical framework of the IT industry. The module covers, e.g., planning and scheduling projects and drawing Gantt charts. Students shall also conduct a research project (including research, paper, literature review, or MSc project proposal, …) and use tools like EndNote and Zotero bibliography manager within MS Word and Latex.
Multi-Core and Multi-Processor Programming (COMP528)
Credits: 15 /
Semester: semester 1
This is a module to cover theoretical and practical aspects of parallel programming for multi-core architectures with the main focus on hand-on programming experience with latest multi-core and multi-processor platforms.
Big Data Analytics (COMP529)
Credits: 15 /
Semester: semester 1
This module provides an initial overview of key algorithms and algorithmic approaches and corresponding software environments used when developing solutions to Big Data problems and explains how to use these to analyse data. A significant portion of statistics, some advanced AI approaches as well as key deterministic and hybrid algorithms are included to support the development of future data analytics and to understand how to develop stochastic, machine learning and hybrid algorithms that can exploit Big Data and can be applied to solve real life problems.
Data Mining and Visualisation (COMP527)
Credits: 15 /
Semester: semester 2
The module covers a range of topics and techniques for analyzing data. Students will learn about different types of data mining problems, including classification, clustering, association pattern mining, and social network analysis, as well as algorithms to solve them.
Students will program selected data mining algorithms from scratch using Python. This hands-on approach will allow them to gain a deeper understanding of how the algorithms work and how they can be applied to real-world datasets. They will experiment with different datasets to see how the algorithms perform and learn how to interpret the results.
MSc Group Project (COMP530)
Credits: 15 /
Semester: semester 2
This module is designed to allow students to consolidate work from the first semester by working as a programming team to realise a solution to a problem related to their programme of study.
Optional modules
Efficient Algorithms (COMP526)
Credits: 15 /
Semester: semester 1
Masters module on practical algorithms and data structures for large datasets.
Optimisation (COMP557)
Credits: 15 /
Semester: semester 1
This module is an in-depth tour over optimisation methods applied for various optimisation models. These methods are extensively used in both academic and industrial practices.
Machine Learning and BioInspired Optimisation (COMP532)
Credits: 15 /
Semester: semester 2
This module teaches you about bio-inspired algorithms for optimisation and machine learning. The algorithms are based on reinforcement learning, DNA computing, brain or neural network models, immune systems, the evolutionary version of game theory, and social insect swarm behaviour such as ant colonies and bee colonies. These techniques are extremely useful for searching very large solution spaces (optimisation) and they can be used to design agents or robots that have to interact and operate in dynamic unknown environments (e.g. a Mars rover, a swarm of robots or network of satellites). The idea of learning optimal behaviour, rather than designing, algorithms and controllers is especially appealing in AI.
Safety and Dependability (COMP524)
Credits: 15 /
Semester: semester 2
Safety and Dependability will cover techniques for the validation of systems against formal specifications. In a first part, safety specifications (something bad never happens) using the Hoare calculus and safe abstraction are covered. A second part refers to termination (something good eventually happens), exploiting well foundedness. In a third part, Markov chains and decision processes are studied, extending the qualitative safety and termination problems from the first part to qualitative/probabilistic properties, and extending them to a simple probabilistic specification language, PCTL. As part of the module, the ability of formulating (probabilistic) models as Markov chains and decision processes are taught, as well as the use of of-the-shelf tools like PRISM or IscasMC for their analysis.
Reasoning About Action and Change (COMP525)
Credits: 15 /
Semester: semester 2
The module introduces the student to the use of logic as a tool for specifying the desired behavior of hardware, software and artificial intelligence systems, and for checking whether a given system does indeed behave as desired. The module enables the student to gain familiarity with a set of techniques which are critical in contemporary industrial applications and in academic research. It consists of 30 lectures and 10 practical sessions.
Algorithmic Game Theory (COMP559)
Credits: 15 /
Semester: semester 2
This module focuses on algorithmic aspects of game theory. A main focus of this module is on the computational aspects in the design of mechanisms and auctions. as part of the module, the students learn about Googles sponsored serarch auctions, which is one of the most successful targeted advertising systems today.
Any optional modules listed above are illustrative only and may vary from year to year. Modules may be subject to minimum student numbers being achieved and staff availability. This means that the availability of specific optional modules cannot be guaranteed.
Year two
Compulsory modules
MSc Industrial Project (COMP599)
Credits: 60 /
Semester: whole session
This module is a major part of the 2 year MSc programmes with a year in industry. It is worth 60 credits. The project takes place in the year 2 during the placement period, typically from September to the following May for a minimum of 26 weeks. An earlier starting date is allowed, but subject to agreement between the University and the placement provider. The module will be assessed by means of: An interim report, An oral presentation, and A final dissertation. The student will be supervised by a university academic as well as an industrial supervisor. This module is aimed at developing the student’s ability to undertake an industrial project in a real world environment successfully and with limited supervision. The student is expected to apply the knowledge acquired from the taught components of the programme and to gain significant knowledge and skills in industry. As a consequence, the expectation is that students’ employability prospects will be greatly enhanced.
MSc Placement Experience (COMP598)
Credits: 60 /
Semester: whole session
This module contains the elements of the Computer Science PGT programmes with a second year industrial placement for the 2 year MSc programmes that are generic to all underlying work experience. The technical elements of the placement are contained in a different module, which is COMP599 MSc Industrial Project.
Any optional modules listed above are illustrative only and may vary from year to year. Modules may be subject to minimum student numbers being achieved and staff availability. This means that the availability of specific optional modules cannot be guaranteed.
How you'll learn
Teaching on the first year of this programme comprises formal lectures, small group tutorials and practical sessions in PC and Mac laboratories. You will also take part in one or more group projects. In your second year, you’ll undertake an industrial project in a real-world environment.
How you're assessed
Modules in the first year of the course are assessed through a combination of examinations and coursework. The examinations take place at the end of each semester and typically take the form of an in-person written assignment, usually to be completed in a couple of hours. You’ll be assigned coursework across the length of each semester. This typically takes the form of class tests, programming assignments or small projects.
The second year of the course is assessed through a portfolio of evidence from your industrial placement and a major project undertaken in your placement setting.
Liverpool Hallmarks
We have a distinctive approach to education, the Liverpool Curriculum Framework, which focuses on research-connected teaching, active learning, and authentic assessment to ensure our students graduate as digitally fluent and confident global citizens.
Course options
Studying with us means you can tailor your degree to suit you. Here's what is available on this course.
The Department of Computer Science is housed in a grade II listed building which has been extensively refurbished for 21st century needs and challenges and provides state-of-the art equipment and high-speed communication links.
A tour of the Computer Science department and facilities
Dr Terry Payne talks you through what you can expect studying Computer Science at the University of Liverpool and shows you some of the facilities and equipment you will be using.
Virtual tour
Supporting your learning
From arrival to alumni, we’re with you all the way:
Careers and employability support, including help with career planning, understanding the job market and strengthening your networking skills
A dedicated student services team can help you get assistance with your studies, help with health and wellbeing, and access to financial advice
Support for students with differing needs from the Disability advice and guidance team. They can identify and recommend appropriate support provisions for you.
An exciting place to study Computer Science
You will be taught by some of the best researchers in the field. In the most recent Research Excellence Framework, the research output of our department was ranked 5th in the UK. This research expertise shows through in our teaching
We teach in state-of-the-art PC and Mac laboratories running a variety of different operating systems, as well as iOS and Android tablets to encourage creativity and innovation within a stimulating environment in which to work and study
Our programmes are continually updated to reflect new technologies and trends.
The programme is accredited by BCS, The Chartered Institute for IT, for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional.
Designed to address a skills gap in the employment market, this MSc will enable you to apply your skills working with big data and your knowledge of high performance computing to real-world challenges.
The MSc has been developed, and is delivered, in close collaboration with the Hartree Centre in Daresbury, near Warrington. Hartree operate the UK’s largest supercomputer, capable of a thousand trillion calculations per second. They collaborate with both industry and the research community to help UK businesses and organisations explore and adopt supercomputing, data science and artificial intelligence technologies.
Career support from day one to graduation and beyond
The transferable skills you develop will also prepare you for a variety of other roles across the IT industry, while your expertise working with data will mean you’re well suited to potential PhD study.
In the UK, a machine learning engineer can expect a graduate entry level salary of £35,000.
With three to five years experience, this can rise to £50,000 to £80,0000.
At senior level or in a specialised or lead role, this can rise to £120,000.
87% of Computer Science students find their main activity after graduation meaningful.
Graduate Outcomes, 2018-19.
Fees and funding
Your tuition fees, funding your studies, and other costs to consider.
Tuition fees
UK fees (applies to Channel Islands, Isle of Man and Republic of Ireland)
Full-time place, per year
£13,300
Year in industry fee
£2,700
International fees
Full-time place, per year
£30,800
Year in industry fee
£6,200
Fees stated are for the 2025-26 academic year.
Tuition fees cover the cost of your teaching and assessment, operating facilities such as libraries, IT equipment, and access to academic and personal support.
If you're a UK national, or have settled status in the UK, you may be eligible to apply for a Postgraduate Loan worth up to £12,167 to help with course fees and living costs. Learn more about fees and funding.
Additional costs
We understand that budgeting for your time at university is important, and we want to make sure you understand any course-related costs that are not covered by your tuition fee. This could include buying a laptop, books, or stationery.
We accept a 2:2 honours degree from a UK university, or an equivalent academic qualification from a similar non-UK institution. This degree should be in computer science or a closely related subject.
International qualifications
If you hold a bachelor’s degree or equivalent, but don’t meet our entry requirements, you could be eligible for a Pre-Master’s course. This is offered on campus at the University of Liverpool International College, in partnership with Kaplan International Pathways. It’s a specialist preparation course for postgraduate study, and when you pass the Pre-Master’s at the required level with good attendance, you’re guaranteed entry to a University of Liverpool master’s degree.
International applicants who do not meet the minimum required standard of English language can complete one of our Pre-Sessional English courses to achieve the required level.
English language qualification
Requirements
IELTS
6.5 overall, with no component below 5.5
Duolingo English Test
120 overall, with no component below 95
Pearson PTE Academic
61 overall, with no component below 59
LanguageCert Academic
70 overall, with no skill below 60
PSI Skills for English
B2 Pass with Merit overall and no band below B2 Pass
INDIA Standard XII
National Curriculum (CBSE/ISC) - 75% and above in English. Accepted State Boards - 80% and above in English.
WAEC
C6 or above
PRE-SESSIONAL ENGLISH
Do you need to complete a Pre-Sessional English course to meet the English language requirements for this course?
The length of Pre-Sessional English course you’ll need to take depends on your current level of English language ability.
Liverpool bursts with diversity and creativity which makes it ideal for you to undertake your postgraduate studies and access various opportunities for you and your family.
To fully immerse yourself in the university experience living in halls will keep you close to campus where you can always meet new people. Find your home away from home.
Discover what expenses are covered by the cost of your tuition fees and other finance-related information you may need regarding your studies at Liverpool.
Contact us
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