This course aims to extend your knowledge gained during undergraduate study with more advanced specialised material reflecting current research at the “cutting-edge” of the discipline.
Introduction
This programme will underpin and enhance your current knowledge and understanding; along with skills that you develop during the programme, will provide you with a strong basis for your future career in the IT industry and towards specialisation in the field of Computer Science related research and development.
Who is this course for?
Designed for graduates of the highest calibre, the MSc in Advanced Computer Science is directed at graduates with a previous Computer Science or IT degree.
What you'll learn
A deep and systematic understanding of selected issues at the forefront of current research in the academic discipline of Computer Science
A depth of knowledge of Computer Science to provide an effective basis for students to continue to a research degree either at The University of Liverpool or elsewhere
A broad-based understanding of current research issues in Computer Science
A comprehensive understanding of how established techniques of research and enquiry are used to extend, create and interpret knowledge in Computer Science and how that knowledge may be applied
The opportunity to participate in current research
An understanding of (research) project management and control.
Accreditation
The programme is accredited by the British Computer Society and is continually updated to reflect new technologies and trends.
Course content
Discover what you'll learn, what you'll study, and how you'll be taught and assessed.
Semester one
Your only compulsory module this semester will help you learn and practice all the necessary skills needed to conduct independent research in computer science which you will need for further learning and your final projects.
You will then select at least three optional modules for the remainder of the semester. You can choose to focus on practical algorithms and data structures for large datasets, how the modern geographic information sciences toolkit can be integrated with Data Science tools to solve practical real-world problems, the fundamentals of how images are generated, represented, compressed and processed, parallel programming for multi-core architectures, optimisation methods, or privacy and security topics such as identification and authentication, monitoring protocols, attacks and defences, legal and ethical issues and future directions.
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.
Optional modules
Knowledge Representation (COMP521)
Credits: 15 /
Semester: semester 1
The module introduces formalisms to reason about knowledge and information. One such formalism is epistemic logic, where one can explicitly represent of what an agent (robot, human, system) knows about the world or about others, as in "I have sent a message, how do I know that it has been received, and that the receiver knows I know this?"
Privacy and Security (COMP522)
Credits: 15 /
Semester: semester 1
The module "Privacy and Security" covers topics such as: identification and authentication, monitoring protocols, attacks and defences, legal and ethical issues and future directions.
Efficient Algorithms (COMP526)
Credits: 15 /
Semester: semester 1
Masters module on practical algorithms and data structures for large datasets.
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.
Geographic Data Science (ENVS563)
Credits: 15 /
Semester: semester 1
This module will introduce students to the nascent field of Geographic Data Science (GDS), a discipline established at the intersection between Geographic Information Science (GIS) and Data Science. The course covers how the modern GIS toolkit can be integrated with Data Science tools to solve practical real-world problems. Core to the set of employable skills to be taught in this course is an introduction to programming tools for GDS in R and Python. The programme of lectures, guided practical classes and independent study illustrate how and why GDS is useful for social science applications.
Image Processing (ELEC319)
Credits: 7.5 /
Semester: semester 1
This module covers the fundamentals of how images are generated, represented, compressed and processed to extract features of interest.
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.
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.
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.
Semester two
You have the chance to choose all of your modules during your second semester, giving you the opportunity to have a bespoke experience.
You could dig into basic algorithmic methods for the design and analysis of algorithms, the algorithmic aspects of game theory, biologically inspired optimisation and introduction to neural networks for artificial intelligence, machine learning, data mining, source coding and error correcting, multi-agent systems, utilising advanced web technologies, use of logic as a tool for specifying the desired behaviour of hardware, software and artificial intelligence systems, game-theoretic discussions of auctions, technical and organisational discussions about cryptography and security, or gain an understanding of how maps can be visualised online.
You’ll also have the chance to participate in a group project where you can work with colleagues as a programming team to build on work from your first semester to find a solution to a relevant problem.
Optional modules
Advanced Algorithmic Techniques (COMP523)
Credits: 15 /
Semester: semester 2
This module aims to teach basic algorithmic methods for design and analysis of algorithms.
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.
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.
Multi-Agent Systems (COMP310)
Credits: 15 /
Semester: semester 2
Multi-agent systems have emerged as one of the most important areas of research and development in information technology in the 1990s. A multi-agent system is one composed of multiple interacting software components known as agents, which are typically capable of co-operating to solve problems that are beyond the abilities of any individual member. Multi-agent systems are important primarily because they have been found to have very wide applicability, in areas as diverse as industrial process control and electronic commerce. This module will begin by introducing the student to the notion of an agent, and will lead them to an understanding of what an agent is, how they can be constructed, and how agents can be made to co-operate effectively with one another to solve problems.
Cloud Computing for E-Commerce (COMP315)
Credits: 15 /
Semester: semester 2
This module will provide an introduction to cloud computing. It will cover physical cloud infrastructure (data-centres, networks and servers), and the software stacks that run on it (containers, micro-services, orchestration and web frameworks).
During the course, students will assemble their own cloud-based application, which will be a webpage with a scalable micro-service-based backend.
Ontologies and Semantic Web (COMP318)
Credits: 15 /
Semester: semester 2
This modules provides a basic introduction to the main principles behind representing and retrieving knowledge effectively on the Web. The module covers the evolution from the standard Web to the Semantic Web, and gives student the opportunity to gain an awareness of the main methods and techniques, including practical awareness, of the main issues arising in annotating web pages with semantic information, in interlinking pages with similar semantic content and in effectively querying these pages.
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.
Information Theory and Coding (ELEC415)
Credits: 7.5 /
Semester: semester 2
This module is aimed to provide an extensive overview of the information theory and coding. Different source codes and channel codes are discussed. Cryptography is also covered.
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.
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.
Web Mapping and Geovisualisation (ENVS456)
Credits: 15 /
Semester: semester 2
Through this module students will gain an understanding of how maps can be visualised online through a number of web platforms. Additionally, the internet will be presented both as a source of new data, and provide analytical functionality that can assist when solving geographic problems. Geographic data can be any dataset that can be visualised in a map. The module is taught through a mixture of lectures and practicals, and is assessed through two summative projects.
Computational Intelligence (COMP575)
Credits: 15 /
Semester: semester 2
Biologically inspired optimisation and introduction to neural networks for artificial intelligence.
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.
Final project
Your final project will give you the opportunity to work independently to explore a substantial problem in depth, making practical use of principles, techniques and methodologies you have acquired during the programme.
You will create a proposal, a presentation, and a final dissertation.
Compulsory modules
MSc Project (COMP702)
Credits: 60 /
Semester: summer
Masters Level final project (individual project with dissertation)
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
You will learn using a combination of formal lectures, small group tutorials and practical sessions in our state-of-the-art PC and Mac laboratories. Throughout the year, you will also take part in one or more group projects. At the end of the year, you will complete a large individual project.
As well as subjects in computer science, you will also develop general skills required for employability in industry or research including teamwork, presentation skills and research techniques.
How you're assessed
Modules are assessed through a combination of examinations and coursework. You will sit examinations at the end of each semester, which are typically in-person written assignments, usually completed over 2 or 2.5 hours. You will complete coursework throughout the semester, typically class tests, programming assignments or small projects.
Lastly, you will submit a final dissertation assessed through a combination of written reports and a presentation of your achievements.
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 (with history going back to the 1960s) is a Centre of Excellence for teaching and research. The latest Research Excellence Framework rated 97% of our research outputs as being world-leading or internationally excellent, the highest proportion of any Computer Science department in the UK.
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.
What students say...
The longer you stay in higher education, the more qualified you’ll be and the more fun you’ll have along the way. You will find it to be the best decision you ever made, after deciding to study for your Bachelor’s degree. I found my undergraduate years to be the best of my life, so doing an extra year at master’s level only prolongs the enjoyment!
Graduating in Advanced Computer Science will provide you with a basis for further career development towards senior technical and managerial positions in the IT industry, and towards specialisation in the field of Computer Science-related research and development.
Career support from day one to graduation and beyond
Job titles and their definitions are not standardised within the IT industry and in a fast changing world employers demand maximum flexibility. However the following are some current options:
Database administrator
Information systems manager
Applications developer
IT consultant
Network engineer
Systems designer.
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
Part-time place, per year
£6,650
International fees
Full-time place, per year
£30,800
Part-time place, per year
£15,400
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
TOEFL iBT
88 overall, with minimum scores of listening 17, writing 17, reading 17 and speaking 19. TOEFL Home Edition not accepted.
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
Have a question about this course or studying with us? Our dedicated enquiries team can help.
