- Entry requirements: Related 2:1 degree (or equivalent)
- Full-time: 24 months
Return to top
Extend your knowledge of computer science on an MSc that will place you at the cutting edge of the discipline. The wide range of options on the programme will enable you to develop expertise in computer science research while tailoring your studies to your own interests, prior to an extended industrial placement in a real-world environment.
Underpinning and enhancing your existing knowledge and understanding of computer science, this MSc will equip you with new skills and provide a strong basis for your future career in the IT industry.
Year one is highly flexible, with one compulsory module that will develop the skills needed to conduct computer science research.
You’ll choose remaining topics from a variety of optional modules. You could opt to focus on practical algorithms and data mining techniques, discover biologically inspired optimisation, hone your expertise in advanced web technologies, or be introduced to neural networks for artificial intelligence.
Whether you’re interested in technical and organisational discussions about cryptography and security or want to enhance your understanding of how maps can be visualised online, the number of options ensures you can tailor the programme to your individual needs.
You’ll also have the chance to participate in a group project where you can work with your peers as part of a programming team to find a solution to a practical problem.
In year two, you’ll undertake an industrial project, that’s research or application oriented, in a real-world environment as part of an extended placement opportunity.
The programme is suitable for graduates whose first degree is in computer science or a closely related subject.
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.
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.
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?"
The module "Privacy and Security" covers topics such as: identification and authentication, monitoring protocols, attacks and defences, legal and ethical issues and future directions.
Biology inspired adaptive algorithms such as Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) play an important role in modern computing, information processing, and machine learning. The latest increase in computer power ensured broad use of the algorithms to solve problems in science and engineering previously considered impossible to tackle. ANNs are now broadly used in pattern recognition, including speech recognition and classification problems, statistics, functional analysis, modelling financial series with considerable stochasticity, etc. GAs are search procedures based on the mechanics of natural selection and natural genetics. They provide effective solutions to a variety of optimisation problems in economics, linguistics, engineering, and computer science. Both ANNs and GAs can exploit massively parallel architectures to speed up problem solving and provide further understanding of intelligence and adaptation.The main goals of the module are to introduce students to some of the established work in the field of Artificial Neural Networks and Genetic Algorithms and their applications, particularly in relation to multidisciplinary research. To equip students with a broad overview of the field, placing it in a historical and scientific context. The module provides students with the knowledge and skills necessary to keep up-to-date in actively developing areas of science and technology and be able to make reasoned decisions.
Masters module on practical algorithms and data structures for large datasets.
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.
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.
This module aims to teach basic algorithmic methods for design and analysis of algorithms.
This module covers the fundamentals of how images are generated, represented, compressed and processed to extract features of interest.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Biologically inspired optimisation and introduction to neural networks for artificial intelligence.
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.
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.
Teaching on the first year of this programme comprises formal lectures, small group tutorials and practical sessions in computer 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.
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.
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.
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.
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.
From arrival to alumni, we’re with you all the way:
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.
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. It also provides a strong foundation for potential PhD research.
Previous graduates are working network systems and data communications analysis, computer software engineering, network and computer systems administration, and database administration.
Potential roles you would be well placed to secure on completion of this MSc include:
Many of our graduates also choose to continue their studies and embark on PhD research.
Your tuition fees, funding your studies, and other costs to consider.
|UK fees (applies to Channel Islands, Isle of Man and Republic of Ireland)|
|Full-time place, per year||£12,400|
|Year in industry fee||£2,500|
|Full-time place, per year||£28,800|
|Year in industry fee||£5,800|
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 paying for your studies..
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.
Find out more about the additional study costs that may apply to this course.
We offer a range of scholarships and bursaries to provide tuition fee discounts and help with living expenses while at university.
The qualifications and exam results you'll need to apply for this course.
My qualifications are from: United Kingdom.
|Postgraduate entry requirements||
You will normally need a 2:1 honours degree, or above, or equivalent. This degree should be in computer science or a closely related subject.
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.
You'll need to demonstrate competence in the use of English language. 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|
View our IELTS academic requirements key.
Standard Level 5
|TOEFL iBT||88 or above with minimum scores in components as follows: Listening and Writing 17, Reading 17, Speaking 19.|
|INDIA Standard XII||National Curriculum (CBSE/ISC) - 75% and above in English. Accepted State Boards - 80% and above in English.|
|Hong Kong use of English AS level||C|
Last updated 27 November 2023 / / Programme terms and conditions