Computer Science MEng, BSc

Course overview

Computer science is a dynamic and fast-moving area of study which opens opportunities in many different industrial sectors. Developments in computer science are radically changing the way that we interact with each other, process data and make decisions.

Successful computer scientists are not only skilled programmers, but they are also highly creative thinkers and problem-solvers who are adept at handling complex information. From commerce to healthcare, AgriTech to government – computing touches every industry, everywhere. That’s why computer scientists are often at the forefront of new technological developments, creating the solutions of tomorrow.

Studying computer science at Leeds will equip you with the core technical and problem-solving skills to tackle current and emerging challenges in this fast-changing field. Alongside technical skills such as algorithm design, problem solving and practical programming, you'll develop a raft of vital workplace skills such as collaborative working and project management. You'll also be taught in our purpose-built hub for students and academics – the SirWilliam Henry Bragg Building – which is home to world-leading research and specialist teaching facilities right here on campus. Explore more of our facilities through our 360 virtual experience.

If you want to be challenged, to work in multidisciplinary teams, solve global and emerging challenges and have a portable and highly sought-after skill set then studying computer science is a great option. The topics you’ll study reflect the latest developments in computer science, equipping you with the key knowledge, skills and experience you need to begin your career in this highly valued profession.

Studying computer science is the perfect foundation for a career in Artificial Intelligence (AI), Machine Learning (ML), Cybersecurity, Software Engineering (full stack development), Blockchain development, Augmented/Virtual Reality or Data Science.

Computer Science provides essential knowledge in algorithms, data structures, and programming—key skills needed to develop Artificial Intelligence systems. Computer science also covers machine learning, neural networks, and big data processing, all of which are critical for building and improving AI models. With AI transforming industries from healthcare to finance, a strong background in computer science opens doors to exciting opportunities in this rapidly growing field..

Why study at Leeds:

• Our globally-renowned research feeds directly into your course, shaping your learning with the latest thinking in areas such as algorithms and complexity, artificial intelligence, computational science and engineering, biomedicine & health and distributed systems and services.
• Experience expert teaching delivered by a programme team made up of academics and researchers who specialise in a variety of computing areas.
• Access excellent facilities including two custom-built teaching laboratories containing high-specification Linux machines and a range of collaborative and quiet study spaces.
• Enhance your career prospects and give your CV that competitive edge before you graduate with our industrial work placement opportunities. Our close industry links have given previous students the chance to work at — and build professional relationships with — organisations such as Apple, Microsoft and Amazon.
• Gain invaluable life experience and advance your personal development with our exciting study abroad programmes, spanning across universities worldwide.
• Make the most of your time at Leeds by joining CompSoc, where you can meet like-minded peers and enjoy a variety of social, professional and academic events including Hackathons, community outreach and professional networking. CompSoc also host sports teams and academic support groups.
• Bring your skills to life outside the classroom through our range of extra-curricular activities. These include a 24-hour hackathon backed by industry sponsors and CompSoc, a hands-on integrated design project, the UKIEPC national programming competition hosted right here on campus, building a rocket with the Leeds University Rocketry Association or attending the British Computing Society’s Women Lovelace Colloquium.

Accreditation

British Computing Society (BCS)

Accreditation is the assurance that a university course meets the quality standards established by the profession for which it prepares its students.

The School of Computer Science at Leeds has a successful history of delivering courses accredited by the British Computing Society (BCS). This means our computer science courses have consistently met the quality standards set by the British Computer Society (BCS).

As we are reviewing our curriculum, we are currently seeking reaccreditation from the BCS for accreditation of full Chartered IT Professional (CITP) and Chartered Engineer (CEng).

Course details and modules

In this course, you'll develop the technical knowledge and practical skills needed to pursue exciting careers across the rapidly evolving technology sector. You'll build a strong foundation in computer hardware, software engineering, and the mathematical principles that underpin modern computing, while developing critical thinking and creative problem-solving abilities valued by employers.

Throughout the course, we work closely with you to support your progress and help you develop the skills required to become a confident, industry-ready computer science graduate. By combining theoretical understanding with practical experience, you'll be prepared to apply your knowledge to real-world challenges and emerging technologies.

You’ll also explore the ethical and societal implications of computing through real-world case studies, encouraging thoughtful discussion around issues such as ethical hacking, open-source software, and the responsible use of personal data.

Whether you aspire to work in areas such as Artificial Intelligence, Cybersecurity, Cloud Computing, or Blockchain technologies, this course will equip you with the foundations, practical expertise, and adaptable skillset needed to build a successful and rewarding career in computing.

Each academic year consists of 120 credits of study.

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 list of typical modules available on this course, please read Computer Sciences MEng, BSc in the course catalogue.

The modules listed below represent typical content and may change over time. Most courses include both compulsory and optional modules, with full details confirmed before the start of each academic year.

Years 1 and 2 focus on developing the fundamental knowledge that underpins all areas of modern computer science. Core topics such as programming, computer systems, algorithms, mathematics and software engineering provide the essential theoretical and practical foundations required to understand and build advanced technologies. While areas such as artificial intelligence, cybersecurity, cloud computing and other emerging fields are highly visible in today’s technology landscape, they rely heavily on these underlying principles. By first establishing strong foundations, students are better prepared to engage with specialist and rapidly evolving topics in their final year and throughout their careers.

Each academic year consists of 120 credits.

Year 1 – Foundations

Programming (40 credits)

Develop core programming and problem-solving skills that form the foundation of modern software development. This module introduces key programming concepts used across industry and prepares you for advanced topics such as software engineering, artificial intelligence and cloud systems.

Topics included:

• Introduction to programming (Python)
• Object-oriented programming and common libraries
• Databases and SQL
• Low-level programming in C

Building our Digital World: Computer Systems and Architecture (40 credits)

Gain a practical understanding of how computers work at the hardware and system level. By exploring how processors, memory and instructions interact, you’ll develop the system-level knowledge required for careers in software engineering, systems programming and high-performance computing.

Topics included:

• Foundations of computer architecture
• Architecture design (building a 16-bit computer from logic gates)
• System programming (machine code and assembly)
• Modern processor architectures and hardware trends

Theoretical Foundations of Computer Science I (40 credits)

Build the mathematical foundations that underpin modern computer science. These concepts support advanced areas such as algorithms, cybersecurity, artificial intelligence and data science, and develop rigorous analytical and problem-solving skills valued across the technology sector.

Topics included:

• Discrete mathematics
• Graph theory and linear algebra
• Calculus
• Algorithms

Year 2 – Developing knowledge and skills

Software Engineering (40 credits)

Develop the practical skills required to design and build large-scale software systems. Through modern programming languages, web technologies and collaborative projects, you’ll gain experience working in development teams and producing software aligned with current industry practices.

Topics included:

• Kotlin programming
• Web-based systems development
• Human–computer interaction and user experience
• Collaborative software engineering projects

Advanced Hardware, Operating Systems and Parallelism (40 credits)

Explore the core technologies that underpin modern computing infrastructure, including operating systems, networks and secure system design. This module develops the systems-level expertise required for careers in cloud computing, cybersecurity, infrastructure engineering and distributed systems.

Topics included:

• Operating systems
• Security and practical cryptography
• Computer networks
• Network and parallel programming

Theoretical Foundations of Computer Science II (40 credits)

Deepen your understanding of algorithms, computation and mathematical modelling. These concepts underpin areas such as machine learning, large-scale data processing and complex software systems, strengthening the analytical and optimisation skills needed in advanced computing roles.

Topics included:

• Algorithm design paradigms
• Further calculus and probability
• Formal languages and theory of computation
• Algorithms and data structures

Year 3 – Specialisation and advanced study

In your final year, you’ll apply the knowledge and skills developed throughout the course to independent and advanced study. You’ll complete a major individual project and explore specialist areas of computer science aligned with current research and industry trends, helping you prepare for careers in areas such as artificial intelligence, cybersecurity, high-performance computing and distributed systems.

Compulsory modules

Professional Innovation and Enterprise (20 credits)

Develop an understanding of professional practice in the technology sector, including ethics, legal responsibilities and commercial awareness. This module prepares you for graduate careers by exploring the wider social, organisational and ethical context of modern computing.

Individual Project (40 credits)

Undertake a substantial independent project under academic supervision, allowing you to investigate a topic aligned with your interests and career goals. You’ll apply research, engineering and analytical skills to design and implement an innovative solution to a real-world computing problem.

Optional modules

You’ll choose from a range of advanced topics that reflect emerging technologies and research strengths within the School. Typical options include:

• High Performance Computing – programming large-scale and accelerated computing systems used in scientific computing and AI.
• Artificial Intelligence and Robotics – design and implementation of intelligent systems and autonomous technologies.
• Neural Networks and Deep Learning – modern machine learning techniques used in areas such as computer vision and natural language processing.
• Optimisation with Applications in Artificial Intelligence – mathematical optimisation techniques used in AI, data science and engineering systems.
• Computer Graphics – techniques used in games, film production, visualisation and interactive applications.
• Resilient Distributed Systems – designing scalable cloud and distributed computing systems.
• Cryptography and Secure Systems – foundations of secure communication, digital security and privacy technologies.
• Algorithms and Complexity – advanced algorithm design and computational problem solving.
• Compiler Design and Optimisation – building compilers and improving the performance of software systems.

Year 4 – Research-led and advanced practice

In your fourth year, you’ll complete a group project. Working as part of a small team you will be paired with an academic to tackle a problem related to your interests and the School of Computer Science’s research expertise. You will also complete a research skills/seminar module where you will develop your skills to engage with cutting edge academic literature.

In year 4, you also have the opportunity to deepen your understanding of the advanced topic modules you studied in year 3. You will be taught by our world-leading research academics and develop an appreciation for the tools and techniques that they apply as part of their research.

Compulsory modules

Group Project (45 credits)

You'll work as part of a group to define a problem and explore a solution. Emphasising teamwork, the module guides you through the development of a collective software project. You’ll engage in planning, coding and project management, gaining practical experience in a real-world, team-based setting. This module enhances problem-solving abilities, communication and project coordination within the context of computer science applications.

Research Seminar (15 credits)

In this research-informed module, you'll embark on an intellectual journey, cultivating research skills and critical thinking. This module fosters an environment where you can engage with cutting-edge topics, explore research methodologies and contribute to scholarly discussions. Through interactive seminars, you’ll refine your ability to critically evaluate existing literature, formulate research questions and design methodologically sound studies. This module nurtures a vibrant research community, with emphasis on collaboration and peer feedback throughout.

This means, once you’ve completed the module, you’ll emerge with enhanced research skills, ready to contribute meaningfully to the ongoing discourse within your respective academic fields.

Optional modules

Please note: The modules listed below are indicative of typical options and some of these options may not be available, depending on other modules you have selected already.

Data Science (15 credits)

Develop an understanding in the methods of analysis used to gain insights from complex data. The module covers the theoretical basis of a variety of approaches, placed into a practical context using different application domains.

Autonomous Systems and Robotics (15 credits)

Explore artificial intelligence concepts, algorithms and methods that can be used by autonomous robots to control behaviour and sense their environment. You'll develop a theoretical understanding of fundamental concepts, as well as practical implementation of algorithms and methods on robot systems.

Cloud Computing Systems (15 credits)

Driven by trends in the consumer internet, cloud computing has become the de facto standard to consume and deliver IT services. Data is becoming larger, with more complex data sets that are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address new business problems. And that’s where cloud computing systems come in.

The module aims to develop a practical understanding of methods, techniques and architectures needed to build big data systems, so that knowledge may be extracted from large heterogeneous data sets. This module is supported by the strong research interest and expertise in cloud and related technologies within the School of Computing and develops expertise in cloud computing and big data systems by giving you the skills and knowledge to design, build and extend the internet infrastructure and to design a variety of applications.

Blockchain Technologies (15 credits)

Learn the 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. Bitcoin is studied as a case study of a long-standing blockchain solution and is considered from a critical perspective on its limitations. Different consensus mechanisms are considered and their trade-offs, including a study of Ethereum and how to develop smart contracts to implement decentralized applications running on a blockchain. You’ll also review incentive mechanisms required to initiate and maintain blockchain projects as well as their crypto economic models and design.

Bio-inspired Computing (15 credits)

This module teaches you how to implement bio-inspired algorithms to solve a range of problems. You’ll design and apply simple genetic algorithms, as well as interpreting the behaviour of algorithms based on the cooperative behaviour of distributed agents with no, or little, central control.

You’ll also consider examples of cooperative phenomena in nature and the concepts of emergence and self-organisation.

Knowledge Representation and Reasoning (15 credits)

Explore the logical foundations of knowledge representation, including key properties of formal systems such as soundness, completeness, expressiveness and tractability. You’ll also learn how to use an automated reasoning tool software tool, build an understanding in automated reasoning and discover how an Ontology can be used within an information system.

Quantum Information Processing (15 credits)

Quantum physics offers the possibility of implementing physical devices that perform computations in a way that is not possible in classical physics. Some of these implementations promise considerable speed ups compared to the classical von Neumann architecture.

This module will discuss elementary concepts of quantum physics that makes quantum information processing possible and explain how they go beyond computational devices based on classical physics. It introduces the mathematical concepts required to reason about quantum information processing, such as complex linear algebra and finite Hilbert spaces. It provides examples of algorithms that – when run on quantum devices – would receive a considerable speedup. You’ll explore the groundbreaking research on physical devices that use quantum information processing and discuss the limitations of technology that is currently available, as well as what is likely to be available within a reasonable timeframe.

Machine Learning (15 credits)

This module covers the principal algorithms used in machine learning using a combination of practical and theoretical sessions. You’ll explore current approaches and gain an understanding of their capabilities and limitations, before evaluating the performance of machine learning algorithms. You’ll also use existing implementations of machine learning algorithms to explore data sets and build models.

Deep Learning (15 credits)

Discover the field of deep learning through a strongly integrative and state-of-the-art approach. In line with the use of AI in key sectors (e.g. finance, health, law), there is an emphasis on the combination of multiple input modalities – specifically combining images, text and structured data. You’ll gain hands-on experience in developing systems to address real-world problems and gain the knowledge and skills necessary to develop an AI system.

Algorithms (15 credits)

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

Data Mining and Text Analytics (15 credits)

Throughout this module, you’ll become familiar with the linguistic theory and terminology of empirical modelling of natural language and the main text mining and analytics application areas. You’ll learn how to use algorithms, resources and techniques for implementing and evaluating text mining and analytics systems. You’ll also develop solutions using open-source and commercial toolkits.

Advanced Software Engineering (15 credits)

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 through the use of patterns and refactoring and gain a broad appreciation of the different architectural styles used in modern software.

Scientific Computation (15 credits)

Understand the range of problems that can be formulated as nonlinear equation systems and explore the role of computational methods in scientific computing with a focus on the importance of reliability, efficiency and accuracy. You’ll consider standard algorithms and the efficiency of their implementation, whilst gaining an understanding in the practical issues associated with code implementation. As you complete the module, you should be able to 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)

Graph theory is a branch of mathematics that interfaces strongly with computer science. It’s developed enormously in recent decades due to its important applications in diverse areas such as transportation, telecommunication, molecular biology, industrial engineering, linguistics, chemistry, etc. Understanding the structural properties of graphs is fundamental for the design of efficient algorithms. This module introduces you to main techniques and results from structural graph theory and considers their algorithmic applications. It covers classical results and more recent ones, introducing current research techniques.

Designing Hardware for Mathematical Computing (15 credits)

Computer arithmetic is at the heart of much computation we perform on digital devices. Building on basic knowledge in computer architectures, this module explores the fundamental principles and techniques underlying the representation and manipulation of numerical data in digital computers. It explores the core concepts of arithmetic operations, numerical formats and precision, laying the groundwork for understanding how computers perform floating-point calculations.

Project work

You'll develop your commercial and industrial awareness by completing real-world problem-solving project work, building up a portfolio of work to demonstrate your knowledge and skills in analysis, communication and teamwork to prospective employers.

Summer internships

During your time at Leeds, you’ll have the opportunity to apply for a paid summer internship, giving you the chance to get involved in research projects to advance your professional skills in research and experimentation.

Want to find out more? Check out what our recent students got up to on their summer internships.

One-year optional work placement or study abroad

During your course, you’ll be given the opportunity to advance your skill set and experience further. You can apply to either undertake a one-year work placement or study abroad for a year, choosing from a selection of universities we’re in partnership with worldwide.

Learning and teaching

In the School of Computer Science, you'll be part of a large and welcoming learning community where academic staff and your fellow students work collaboratively together. Our expert academic staff bring a wealth of industrial and research experience meaning you'll have awareness of the forefront of developments when you graduate.

You'll be joining a diverse community of computer scientists from a range of backgrounds, where you'll be encouraged to share your experiences with and to learn from others in order to develop a university culture where our differences are our strengths. Our research feeds directly into our teaching, meaning you'll learn about the very latest developments in your subject while gaining the knowledge and skills to meet the needs of your graduate job.

To help you benefit from our expertise, you'll be engaged in a mix of lectures, tutorials, seminars and practical labs, complemented by online learning resources and project-based learning. This mix of activities will develop you into a flexible and agile learner, suitable for keeping up with the fast pace of development in graduate careers. The approach is inclusive by design, and you'll be supported to develop the skills to best benefit from each type of activity.

Our personal tutorial system will provide you with academic and pastoral support. You'll be assigned to an academic personal tutor who will mentor you throughout your studies at Leeds. Everyone will have a different set of experience, interests and motivations for studying the subject, and your personal tutor will help you to understand what these are and how you can best leverage your experiences to make the most of your time at Leeds.

Specialist facilities

You’ll study in the Sir William Henry Bragg Building which offers a wealth of facilities to support your learning. It has two custom-built teaching laboratories containing high-specification Linux machines – sufficient to complete all work asked of you on our programmes. In addition, the Sir William Henry Bragg Building houses our state-of-the-art research laboratories which are used by our internationally leading researchers and postgraduate students – and are available to students as part of their final year individual project.

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 variety of methods which are chosen to emulate real-life tasks or activities you are likely to encounter in a graduate career. This may include time-constrained assessments, laboratory practicals, reports, problem-solving worksheets, projects and presentations.

Where possible, assessment is designed to be contemporary with recent events and developments in computer science – making them interesting and relevant.

We use summative assessment, which contributes to your degree outcome, as well as formative assessment, which does not contribute to your degree outcome but provides an indication of performance. This combination allows you to become comfortable with the style of assessment and allows us to provide targeted additional support where it is required. Your work will be assessed by a member of academic staff who’ll provide feedback on what you did well, areas of improvement and stretch goals. This feedback may be in written or verbal form.

Our assessment approach is designed to be inclusive by default, however, we also make reasonable adjustments where required.

Entry requirements

A-level: AAA including Mathematics.

Where an A-level Science subject is taken, we require a pass in the practical science element, alongside the achievement of the A-Level at the stated grade.

GCSE: English Language grade 4 (C) or higher, or an equivalent English language qualification. We will accept Level 2 Functional Skills English instead of GCSE English.

Extended Project Qualification (EPQ), International Project Qualification (IPQ) and Welsh Baccalaureate Advanced Skills Challenge Certificate(ASCC): We recognise the value of these qualifications and the effort and enthusiasm that applicants put into them, and where an applicant offers an A in the EPQ/IPQ/ASCC we may make an offer of AAB at A-Level including A in Mathematics.

Alternative qualification

Read more about UK and Republic of Ireland accepted qualifications or contact the School’s Undergraduate Admissions Team.

Alternative entry

We’re committed to identifying the best possible applicants, regardless of personal circumstances or background.

Access to Leeds is a contextual admissions scheme which accepts applications from individuals who might be from low income households, in the first generation of their immediate family to apply to higher education, or have had their studies disrupted.

If you live in a neighbourhood where there is low participation in higher education, we may be able to give priority to your application.

Find out more about Access to Leeds and contextual admissions.

Typical Access to Leeds A Level offer: ABB, including an A in Mathematics and a pass in the Access to Leeds scheme.

Foundation years

If you do not have the formal qualifications for immediate entry to one of our degrees, you may be able to progress through a Foundation Year. A Foundation Year is the first year of an extended degree. We’ve designed these courses for applicants whose backgrounds mean they are less likely to attend university and who don’t meet the typical entry requirements for an undergraduate degree.

We offer a Studies in Science with Foundation Year BSc for students without science and mathematics qualifications.

You could also study our Interdisciplinary Science with Foundation Year BSc which is for applicants whose background is less represented at university.

On successful completion of your Foundation Year, you will be able to progress onto your chosen course.

Alternative Entry Scheme for Mature Applicants

If you are a mature applicant and you don’t have the required A Levels or GCSE English and Math qualifications, you can complete our Alternative Entry Scheme (subject to meeting the eligibility criteria for the scheme). As part of this, you may be asked to take tests in English and maths and to write an essay.

Further information on the support available for mature students can be found at https://www.leeds.ac.uk/mature-students.

For alternative qualification offers please contact the admissions team.

International

We accept a range of international equivalent qualifications. For more information, please contact the Admissions Team.

International Foundation Year

International students who do not meet the academic requirements for undergraduate study may be able to study the University of Leeds International Foundation Year. This gives you the opportunity to study on campus, be taught by University of Leeds academics and progress onto a wide range of Leeds undergraduate courses. Find out more about International Foundation Year programmes.

English language requirements

IELTS 6.0 overall, with no less than 5.5 in each section.. For other English qualifications, read English language equivalent qualifications.

Improve your English
If you're an international student and you don't meet the English language requirements for this programme, you may be able to study our undergraduate pre-sessional English course, to help improve your English language level.

Fees

UK: £10,050

International: To be confirmed

The amount of tuition fees you pay is based on whether you are classified as a home (UK) or international student. Find out how we assess your fee status.   

Tuition fees for UK students 
Tuition fees for UK undergraduate students starting in 2026/27 are £9,790 and £10,050 for students starting in 2027/28.  

Subsequent years 
The UK government sets the maximum tuition fee caps that universities can charge UK students. This means your tuition fee in future academic years will reflect any changes set by the government.   

From 2028/29 onwards, tuition fees are likely to increase annually, at least in line with inflation, and may rise further if the government increases the fee cap.   

Tuition fees for international students 
The international fee applies for each year of full-time study and will remain the same for the duration of your course.    

Read more about tuition fees.

Tuition fees for a study abroad or work placement year
If you take a study abroad or work placement year, you’ll pay a reduced tuition fee during this period. For more information, see Study abroad and work placement tuition fees and loans.

Read more about paying fees and charges.

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 is help for students in the form of loans and non-repayable grants from the University and from the government. Find out more in our Undergraduate funding overview.

Scholarships are also available to help fund your degree. Find out more and check your eligibility below:

• Scholarships for International students
• Scholarships for UK students
• Your subject area may also offer scholarships

Applying

Apply to this course and check the deadline for applications through the UCAS website.

We may consider applications submitted after the deadline. Availability of courses in UCAS Extra will be detailed on UCAS at the appropriate stage in the cycle.

Admissions guidance

Read our admissions guidance about applying and writing your personal statement.

What happens after you’ve applied

You can keep up to date with the progress of your application through UCAS.

UCAS will notify you when we make a decision on your application. If you receive an offer, you can inform us of your decision to accept or decline your place through UCAS.

How long will it take to receive a decision

We typically receive a high number of applications to our courses. For applications submitted by the January UCAS deadline, UCAS asks universities to make decisions by mid-May at the latest.

Offer holder days

If you receive an offer from us, you’ll be invited to an offer holder day. This event is more in-depth than an open day. It gives you the chance to learn more about your course and get your questions answered by academic staff and students. Plus, you can explore our campus, facilities and accommodation.

International applicants

International students apply through UCAS in the same way as UK students.

We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

Read about visas, immigration and other information here.

If you’re unsure about the application process, contact the admissions team for help.

Admissions policy

University of Leeds Admissions Policy 2026

This course is taught by

School of Computer Science

Contact us

School of Computer Science Undergraduate Admissions

Email: ugcomp@leeds.ac.uk

Career opportunities

There’s a wealth of excellent job opportunities for graduate computer scientists – making it easy for you to choose your ideal career.

From start-ups to international organisations and non-governmental organisations, the computing industry is always looking for computer science graduates to realise the next opportunity.

Our graduates find employment across a range of sectors including:

• Non-governmental organisations
• Government agencies
• Education
• Media
• Technology
• Consultancies
• Finance (& Finance Technologies)
• Public Authority
• Retail
• Research & Development

Careers support

Study abroad and work placements

Study abroad

Studying abroad is a unique opportunity to explore the world, whilst gaining invaluable skills and experience that could enhance your future employability and career prospects too.

From Europe to Asia, the USA to Australasia, we have many University partners worldwide you can apply to, spanning across some of the most popular destinations for students.

This course offers you the chance to spend time abroad, usually as an extra academic year between years 2 and 3 which will extend your studies by 12 months.

Once you’ve successfully completed your year abroad, you'll be awarded the ‘international’ variant in your degree title which demonstrates your added experience to future employers.

Find out more at the Study Abroad website.

Work placements

A placement year is a great way to help you decide on a career path when you graduate. You’ll develop your skills and gain a real insight into working life in a particular company or sector. It will also help you to stand out in a competitive graduate jobs market and improve your chances of securing the career you want.

Benefits of a work placement year:

• 100+ organisations to choose from, both in the UK and overseas
• Build industry contacts within your chosen field
• Our close industry links mean you’ll be in direct contact with potential employers
• Advance your experience and skills by putting the course teachings into practice
• Gain invaluable insight into working as a professional in this industry
• Improve your employability

If you decide to undertake a placement year, this will extend your period of study by 12 months and, on successful completion, you will be awarded the ‘industrial’ variant in your degree title to demonstrate your added experience to future employers.

With the help and support of our dedicated Employability Team, you can find the right placement to suit you and your future career goals.

Here are some examples of placements our students have recently completed:

• Arm
• HP inc UK
• GlaxoSmithKline Research & Development
• UK Research & Innovation
• Apple
• Microsoft
• Amazon
• PwC

Find out more about Industrial placements.