- Entry requirements: 2:1 degree (or equivalent)
- Full-time: 12 months
- Part-time: 24 months
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If you didn’t study computer science at degree level, this MSc combines a wide-ranging introduction to the analysis, design and implementation of computer systems, with a comprehensive understanding of cutting-edge research. You'll be immersed in software design, programming, datasets, information systems and web applications and develop all the skills needed to conduct independent research in computer science
This MSc provides a depth of knowledge in computer science, underpinned by a thorough understanding of key issues at the forefront of current research in this discipline.
You’ll learn how to design and create software, gain experience of modern programming languages, and discover how databases are used in modern information systems, from supermarket checkouts to online banking.
We’ll also equip you with a good understanding of the most significant technologies for developing web applications. These include HTML, cascading style sheets, computer-generated imagery (CGI) programming, and PHP/SQL programming.
Further opportunities to specialise and enhance your knowledge are available through a range of optional modules. You could choose to focus on topics including artificial intelligence, biologically inspired optimisation, neural networks, data mining, machine learning, multi-agent systems, e-commerce, online map visualisations, or software safety and dependability.
You’ll have the opportunity to work as part of a small group on a practical project to find a solution to a computer science problem. We’ll also provide a thorough grounding in how to plan and conduct research in preparation for your dissertation.
This MSc is suitable for graduates with a science or engineering background, such as a degree in mathematics or physical sciences, who wish to build upon the IT skills and knowledge gained during undergraduate study. The programme is not suitable for computer science graduates.
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.
International students may be able to study this course on a part-time basis but this is dependent on visa regulations. Please visit the Government website for more information about student visas.
If you're able to study part-time, you'll study the same modules as the full-time master's degree over a longer period, usually 24 months. You can make studying work for you by arranging your personal schedule around lectures and seminars which take place during the day. After you complete all the taught modules, you will complete your final dissertation or project and will celebrate your achievements at graduation the following term.
Studying part-time means you can study alongside work or any other life commitments. You will study the same modules as the full-time master's degree over a longer period, usually 24 months. You can make studying work for you by arranging your personal schedule around lectures and seminars which take place during the day. After you complete all the taught modules, you will complete your final dissertation or project and will celebrate your achievements at graduation the following term.
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 aim of COMP517 is to help you to learn how to design and create software. Central to this will be an understanding of and practical experience with a modern programming language, but you will also be made aware of the importance of using sound software engineering techniques to develop high quality programs. As with many endeavours (swimming, chess-playing, story-writing) programming is a skill that must be learned and improved upon by constant practice. In this module, therefore, the emphasis will be on self-study. Although lectures will be used to introduce the various topics, you will be expected to spend the majority of your time in reading the corresponding textbook chapters, attempting numerous exercises, and completing the specified assignments.
This module focuses on how databases are used in modern information systems. They are at the heart of almost all systems, such as supermarket checkouts, online banking, home rentals, and much more. One of the most successful data definition and manipulation languages is SQL, which will be covered in detail. The module will also introduce some of the fundamental concepts in computer science, as well as the mathematical underpinnings of relational databases and the techniques used to support concurrency and reliability in large information systems.
Masters module on practical algorithms and data structures for large datasets.
Masters level introductory web programming module covering such topics as HTML, Cascading Style Sheets, CGI programming, and PHP/SQL programming.
Biologically inspired optimisation and introduction to neural networks for artificial intelligence.
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 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 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.
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.
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.
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.
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.
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.
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.
Masters Level final project (individual project with dissertation)
Teaching on 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. At the end of the year, you’ll complete a major individual research project under expert supervision.
Modules 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.
Your dissertation is assessed through a combination of written reports and a presentation of your achievements.
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.
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 MSc in Computer Science requires spending a large amount of time programming in different languages and running complex sets of code that demand powerful hardware resources. The computer labs at the University of Liverpool provide me with powerful PCs with every piece of software I require to complete my assignments.
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.
You’ll graduate ready for a wide range of careers in the IT industry. You may wish to join the many students who seek employment at the interface of the IT domain and the subject matter of your first degree. The programme 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|
|Part-time place, per year||£6,200|
|Full-time place, per year||£28,800|
|Part-time place, per year||£14,400|
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 a science or engineering related subject, such as mathematics or physical sciences, but should not be in computer science.
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 18 October 2023 / / Programme terms and conditions