Course overview

Computer science is more than just programming. It is about problem-solving and creativity. Our range of optional modules allows you to explore the areas of computer science that excite you. These include user experience design, virtual reality, artificial intelligence and machine learning.

You'll take part in a group project in year two which prepares you for designing and creating the computer systems of the future. Many projects are in collaboration with industry. Previous students have worked with Capital One, Experian, IBM and UniDays. This is great for your CV and can help you make contacts ready for when you start your career.

The benefit of this course is you'll spend your third year abroad. You could be studying in Australia, Canada, Hong Kong, Ireland, Mexico, New Zealand or Singapore.

You may recognise some of our tutors from the Computerphile YouTube series. It is this inspiring teaching that you can expect at Nottingham. 

Why choose this course?

Average salary


Average starting salary for computer science graduates. HESA Graduate Outcomes 2020, using methodology set by The Guardian


by the British Computer Society

Scholarships available

up to 50% off your tuition fees.


to transfer between computer science degrees during year one

No experience

in programming is needed to apply for this course

Study abroad

in year three. You'll gain amazing life experiences and learn skills.

Entry requirements

All candidates are considered on an individual basis and we accept a broad range of qualifications. The entrance requirements below apply to 2022 entry.

UK entry requirements
A level AAA (AAB if you have an A in computer science/computing)
Required subjects

GCSE Maths at grade B and GCSE English at grade C

IB score 36 with 5 in maths at Standard/Higher Level or GCSE maths, 5 (B) or above. 34 with 6 in computer science at Higher Level, and 5 in maths at Standard/Higher Level or GCSE maths, 5 (B) or above

A levels

AAA (AAB if you have an A in computer science/computing). Please note that A level ICT or IT do not qualify for the lower level.


Maths at grade B and GCSE English at grade C

Foundation progression options

If you don't meet our entry requirements there is the option to study the engineering and physical sciences foundation programme. If you successfully pass the year, you can progress to any of our computer science courses. There is a course for UK students and one for EU/international students.

Learning and assessment

How you will learn

Teaching methods

  • Computer labs
  • Lectures
  • Tutorials

How you will be assessed

You will be given a copy of our marking criteria which provides guidance on how your work is assessed. Your work will be marked in a timely manner and you will receive regular feedback. The pass mark for each module is 40%.

Your final degree classification will be based on marks gained for your second and subsequent years of study. Year two is worth 20% with year three and four worth 40% each. 

Assessment methods

  • Coursework
  • Group project
  • Research project
  • Written exam

Contact time and study hours

As a guide, one credit equals approximately 10 hours of work. You will spend around half of your time in lectures, tutorials, mentoring sessions and computer labs. The remaining time is spent in independent study. Tutorial groups are usually made up of eight students. They meet every other week during term-time. Core modules are taught by a mixture of professors, associate professors and teaching associates with help from PhD students and research staff.

Study abroad

Students who choose to study abroad are more likely to achieve a first-class degree and earn more on average than students who did not (Gone International: Rising Aspirations report 2016/17).

Benefits of studying abroad

  • Explore a new culture
  • A reduced tuition fee of up to 80% for the time you are abroad
  • Improve your communication skills, confidence and independence 

Countries you could go to

You can apply to spend your third year in countries such as:

  • Australia
  • Canada
  • Hong Kong
  • Ireland
  • Mexico
  • New Zealand
  • Singapore

All teaching is in English. You must achieve a minimum 55% pass rate to go on the year abroad.

Year in industry

Choose our industry year course and you could join previous students who have worked at Capital One, ASOS and Experian.

A year in industry gives you the opportunity to spend a year on placement with an industrial partner. This can help improve your employability and experience working in a real company

You will be supported by the University as you apply for placements.

Aaron Osher

Aaron talks about why he chose to study computer science at Nottingham.


In the first year you will learn the foundations of computer science. You will be introduced to programming languages such as C, Java and Haskell. We don't expect you to have programmed before so you don't need to worry if you have no experience. 

Mathematics for Computer Scientists

You’ll cover the basic concepts in mathematics which are of relevance to the computer scientists.

These include:

  • logic
  • sets
  • functions and relations
  • graphs
  • induction
  • basic probability
  • statistics and matrices
Systems and Architecture

This module runs alongside 'Computer Fundamentals' and provides an expanded view by considering how real computer systems (such as ARM, x86, Linux and *BSD) and networks work.

You’ll also cover the principles of the lower level implementation of I/O using polling and interrupts, and the use of exceptions; how memory and storage are organized as well addressing the issues arising from multicore systems. 

You’ll spend around five hours per week in tutorials, lectures and computer classes.

Programming and Algorithms

The module introduces basic principles of programming and algorithms. It covers fundamental programming constructs, such as types and variables, expressions, control structures, and functions.

You'll learn how to design and analyse simple algorithms and data structures that allow efficient storage and manipulation of data. You'll also become familiar with basic software development methodology.

You will spend around six hours per week in lectures, computer classes and tutorials.

Computer Fundamentals

You will gain a basic understanding of the fundamental architecture of computers and computer networks.

You’ll learn how the simple building blocks of digital logic can be put together in different ways to build an entire computer.

You’ll also learn how modern computer systems and networks are constructed of hierarchical layers of functionality which build on and abstract the layers below.

You will spend five hours per week in tutorials, lectures and computer classes.

Introduction to Software Engineering MSc

You will be introduced to the concept of software engineering and will be taken through the software development process: deciding exactly what should be built (requirements and specification), designing how it should be built (software architecture), development strategies (implementation and testing), and maintaining change (software evolution and maintenance).

Database and Interfaces

This module considers both the structure of databases, including how to make them fast, efficient and reliable, and the appropriate user interfaces which will make them easy to interact with for users. You will start by looking at how to design a database, gaining an understanding of the standard features that management systems provide and how you can best utilise them, then develop an interactive application to access your database.

Through the lectures and computing sessions you will learn how to design and implement systems using a standard database management system, web technologies and GUI interfaces through practical programming/system examples.

Programming Paradigms

In this module you will learn the basic principles of the object-oriented and functional approaches to programming, using the languages Java and Haskell. You will also see how they can be used in practice to write a range of different kinds of programs.

Fundamentals of Artificial Intelligence

You will gain a broad overview of the fundamental theories and techniques of artificial intelligence (AI).

You’ll explore how computers can produce intelligent behaviour, and will consider topics such as the history of AI, AI search techniques, neural networks, data mining, philosophical and ethical issues, and knowledge representation and reasoning.

You will spend two hours per week in lectures for this module. 

Mathematics for Computer Scientists 2

You'll cover the following basic concepts in mathematics which are of relevance to the development of computer software. Topics which will be covered include linear algebra and calculus. 

The above is a sample of the typical modules we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Modules (including methods of assessment) may change or be updated, or modules may be cancelled, over the duration of the course due to a number of reasons such as curriculum developments or staffing changes. Please refer to the module catalogue for information on available modules. This content was last updated on Wednesday 24 November 2021.

Core modules

Operating Systems and Concurrency

 This course covers the fundamental principles that underpin operating systems and concurrency. Topics covered include the architecture of operating systems, process and memory management, storage, I/O, and virtualisation. The principles of concurrency will be introduced from both the perspective of an operating system and user applications. Specific topics on concurrency include: hardware support for concurrency; mutual exclusion and condition synchronisation; monitors; safety and liveness properties of concurrent algorithms, and the use of threads and synchronisation.

Software Engineering Group Project

Working in groups of around five to six people, you’ll be assigned a supervisor who will provide you with a short written description of a computer application to be designed, programmed, and documented during the course of the module. Each group will meet twice a week, once with your supervisor and once without; you’ll also have four introductory one hour lectures. 

Algorithms, Correctness and Efficiency

This module covers important aspects of algorithms, namely their correctness and efficiency.

You’ll study topics such as:

  • proofs in propositional logic and predicate logic
  • classical vs. intuitionistic reasoning
  • basic operations on types
  • verification of list based programs
  • introduction to program specification and program correctness

To address the issue of efficiency we cover the use of mathematical descriptions of the computational resources needed to support algorithm design decisions. The emphasis is upon understanding data structures and algorithms so as to be able to design and select them appropriately for solving a given problem.

Languages and Computation

You'll investigate classes of formal language and the practical uses of this theory, applying this to a series of abstract machines ultimately leading to a discussion on what computation is and what can and cannot be computed.

You'll focus in particular on language recognition, but will study a range of topics including:

  • finite state machines
  • regular expressions
  • context-free grammars
  • Turing machines
  • Lambda calculus

This module builds on parts of the ACE module addressing data structures and formal reasoning and introduces concepts which are important to understand the analysis of algorithms in terms of their complexity.

Developing Maintainable Software

To build on first year programming modules and further develop programming ability and experience, including ability to develop and understand a large piece of software, build user interfaces and follow a realistic design and testing procedure.

Topic examples include: design diagrams and modelling; GUI programming; testing software engineering methodologies (including agile development and tools), refactoring; design patterns and SOLID principles; all in the context of understanding anddeveloping maintainable third-party code. You will spend around three hours per week in lectures and two hours per week in computer classes studying for this module.

Optional modules

Artificial Intelligence Methods

This module builds on the Fundamentals of Artificial Intelligence module. The emphasis is on building on the AI research strengths in the School.

You will be introduced to key topics such as AI techniques, fuzzy logic and planning, and modern search techniques such as Iterated Local Search, Tabu Search, Simulated Annealing, Genetic Algorithms, and Hyper-heuristics, etc.

You will also explore the implementation of some AI techniques.

Introduction to Human Computer Interaction

An overview of the field of human computer interaction which aims to understand people's interactions with technology and how to apply this knowledge in the design of usable interactive computer systems.

The module will introduce the concept of usability and will examine different design approaches and evaluation methods.

Advanced Functional Programming

Building upon the introductory Functional Programming module in year one, you’ll focus on a number of more advanced topics such as: 

  • programming with effects
  • reasoning about programs
  • control flow
  • advanced libraries
  • improving efficiency
  • type systems
  • functional pearls

You’ll spend around four hours per week in lectures and computer classes.

Introduction to Image Processing

This module introduces the field of digital image processing, a fundamental component of digital photography, television, computer graphics and computer vision.

You’ll cover topics including:

  • image processing and its applications
  • fundamentals of digital images
  • digital image processing theory and practice
  • applications of image processing

You’ll spend around three hours in lectures and computer classes each week.

C++ Programming

You will cover the programming material and concepts necessary to obtain an understanding of the C++ programming language. You will spend around four hours per week in lectures and computer classes and will be expected to take additional time to practice and to produce your coursework.

Software Specification

You will cover two main aspects of the software engineering process in depth: requirements and design. This will cover modern approaches to large scale requirements and engineering and specification and approaches to systems and architectural design. 

Distributed Systems

This module covers the following topics:

  • overview of parallel and distributed computing
  • applications of distributed systems
  • fundamental concepts of distributed systems (processes and message passing, naming and discovery, fault tolerance and partial failure, consistency and cacheing, security)
  • reliable network communication
  • distributed system design approaches (direct vs indirect communication, client-server vs peer-to-peer, stateful vs stateless interfaces)
  • introduction to distributed data management
  • introduction to distributed algorithms
Artificial Intelligence Methods (10cr)

This module builds on the first year Introduction to AI, which covers the ACM learning outcomes, and introduces new areas. The emphasis is on building on the AI research strengths in the School. As a Launchpad it gives brief introductions to topics including AI techniques, fuzzy logic and planning, and modern search techniques such Iterated Local Search, Tabu Search, Simulated Annealing, Evolutionary Algorithms, Genetic Algorithms and Hyper-heuristics, etc.

The above is a sample of the typical modules we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Modules (including methods of assessment) may change or be updated, or modules may be cancelled, over the duration of the course due to a number of reasons such as curriculum developments or staffing changes. Please refer to the module catalogue for information on available modules. This content was last updated on

This is the year you'll spend abroad.

Optional modules

Advanced Algorithms and Data Structures

You'll study the theory used in the design and analysis of advanced algorithms and data structures. Topics covered include string algorithms (such as for string matching, longest common subsequence), graph algorithms (such as for minimum cuts and maximum flows, and Google's pagerank algorithm), advanced data structures (such as Fibonacci heaps and Bloom filters), and randomised search heuristics (evolutionary algorithms). You'll learn all the necessary probability theory will be introduced, including random variables and concentration inequalities.

The theory is practiced in weekly labs where we learn how to implement the algorithms and data structures as functional and imperative programs (using the languages Haskell and C), and apply these to solve large instances of real-world problems. 

Advanced Computer Networks

This module will provide you with an advanced knowledge of computer communications networks, using examples from all-IP core telecommunications networks to illustrate aspects of transmission coding, error control, media access, internet protocols, routing, presentation coding, services and security.

The module will describe Software Defined Networks (SDNs) and provide examples of using them to enable very large scale complex network control. It will also provide advanced knowledge of various routing and query protocols in:

  • Ad Hoc Networks
  • Mobile Ad Hoc Networks (MANETs)
  • Vehicular Ad Hoc Networks (VANETs)
  • Disconnection/Disruption/Delay Tolerant Networks (DTNs)
  • impact of new networking developments, such as security risks, ethics, interception and data protection will be reflected and discussed systematically
Autonomous Robotic Systems

This module introduces you to the computer science of robotics, giving you an understanding of the hardware and software principles appropriate for control and localisation of autonomous mobile robots. A significant part of the module is laboratory-based, utilising physical robotic hardware to reinforce the theoretical principles covered. You will cover a range of topics including basic behavioural control architectures, multi-source data aggregation, programming of multiple behaviours, capabilities and limitations of sensors and actuators, and filtering techniques.

Project in Advanced Algorithms and Data Structures

This project involves a self-guided study of a selected advanced algorithm or data structure. The outcome of the project is an analysis and implementation of the algorithm or data structure, as well as an empirical evaluation, preferably on a real-world data set of significant size.

Linear and Discrete Optimisation

This module provides an entry point to computational optimisation techniques, in particular for modelling and solving linear and discrete optimisation problems like diet optimisation, network flows, task assignment, scheduling, bin-packing, travelling salesmen, facility location, vehicle routing and related problems.

In this module, you will learn to interpret and develop algebraic models for a variety of real-world linear and discrete optimisation problems to then use powerful optimization software (linear, integer and mixed-integer solvers) to produce a solution.

The module covers topics such as:

  • linear programming
  • integer programming
  • combinatorial optimisation
  • modelling and optimisation software
  • multi-objective optimisation 

Optimisation technology is ubiquitous in today's world, for applications in logistics, finance, manufacturing, workforce planning, product selection, healthcare, and any other area where the limited resources must be used efficiently. Optimisation enables prescriptive analytics in order to support and automate decision-making.

Real-world Functional Programming

This module introduces tools, techniques, and theory needed for programming real-world applications functionally, with a particular emphasis on the inherent benefits of functional programming and strong typing for reuse, maintenance, concurrency, distribution, and high availability. These are all aspects that have contributed to the popularity of functional programming for demanding applications eg in the finance industry and have also had a significant impact on the design of many modern programming languages such as Java, C#, and Rust, and frameworks such as MapReduce and React.

Topics typically include functional design patterns, pure data structures, reactive programming, concurrency, frameworks for web/cloud programming, property-based testing, and embedded domain-specific languages. The medium of instruction is mainly Haskell, but other functional languages, for example, Erlang, may be used where appropriate and for a broader perspective.

If you wish to study some particular topic in scope of this module in more depth, you are encouraged to consider taking the module Real-world Functional Programming Project.

Real World Functional Programming Project MSc

If you choose Real-world Functional Programming, this module allows you to explore a real-world functional programming topic of your choice in depth through a programming project.

Specifically, there are no requirements regarding the programming language used. The language would not even necessarily have to be a functional one. What is important is that the ideas underpinning the project are related to real-world functional programming. You will need to define your project through a project pitch. 

Individual Programming Project

You will undertake a programming project relevant for AI for an External Client under the supervision of an academic member of staff.

The client, which can be a company, charity, research group etc., provides a problem that requires a sufficiently challenging piece of software to be developed. The client and project idea could be provided by the students or the supervisor. Each project must ultimately be agreed with the concerned Supervisor.

The main assessed outputs are the developed software, including any end-user documentation, along with a 15,000-word document that outlines the development, design and implementation of the software, highlighting the most interesting aspects.

The software must be developed in a professional and systematic manner appropriate for the problem domain.

The assessment is informed by a statement from the External Client on how well the developed software addresses the problem.

Group Programming Project

Students undertake a programming project for an external client in self-formed groups of two to four students under the supervision of an academic member of staff. The client, which can be a company, charity, research group etc., but not the supervisor, provides a problem that requires a sufficiently challenging piece of software to be developed. The client and project idea could be provided by the students or the supervisor. However, projects must have aspects that are relevant to each student's programme of study; eg, there needs to be an artificial intelligence (AI) aspect if any AI students are involved.

The main assessed outputs are the developed software, including any end-user documentation, along with a 5,000-word document that outlines the development, design and implementation of the software, highlighting the most interesting aspects. The software must be developed in a professional and systematic manner appropriate for the problem domain. The assessment is informed by a statement from the external client on how well the developed software addresses the problem. Additionally, each student submits an individual 5,000-word report explaining his or her own contributions and giving a critical appraisal of how the project went, including group dynamics and the contributions of others.

Individual Research Project

Students undertake a research project in computer science supervised by an academic member of staff. The topic should fall within the supervisor's research interests and must further be relevant to the student's programme of study; in particular, projects undertaken by artificial intelligence (AI) students must have a strong AI focus. The project may be proposed by either the supervisor or the student, and may be theoretical, empirical, or even of survey type depending on what is appropriate and feasible for the area and topic. Projects, however, must ultimately be agreed with the supervisor concerned.

The results from the project are to be distilled into a conference-format research paper, authored by the student and constituting the main assessed output. There may, however, be further deliverables as dictated by the nature of the project. Any such deliverables are to be submitted (electronically) as supplementary material. A revised version of the paper, possibly co-authored with the supervisor, may subsequently be submitted for publication to an external venue, such as a conference or journal, if the work is judged to be of sufficiently high standard. 


This module covers the history, development and state-of-the-art in computer games and technological entertainment.

You will gain an appreciation of the range of gaming applications available and be able to chart their emergence as a prevalent form of entertainment. You will study the fundamental principles of theoretical game design and how these can be applied to a variety of modern computer games.

In addition, you will study the development of games as complex software systems. Specific software design issues to be considered will include the software architecture of games, and the technical issues associated with networked and multiplayer games.

Finally, you will use appropriate software environments to individually develop a number of games to explore relevant theoretical design and practical implementation concepts.

Data Modelling and Analysis

This module will enable you to appreciate the range of data analysis problems that can be modelled computationally and a range of techniques that are suitable to analyse and solve those problems.

Topics covered include:

  • basic statistics
  • types of data
  • data visualisation techniques
  • data modelling
  • data pre-processing methods including data imputation
  • forecasting methods
  • clustering and classification methods (decision trees, naīve bayes classifiers, k-nearest neighbours)
  • data simulation
  • model interpretation techniques to aid decision support

Spending around four hours each week in lectures and computer classes, appropriate software (eg. R, Weka) will be used to illustrate the topics you'll cover.

Fuzzy Logic and Fuzzy Systems

This module aims to provide a thorough understanding of fuzzy sets and systems from a theoretical and practical perspective.

Topics commonly include:

  • type-1 fuzzy sets
  • type-1 fuzzy logic systems
  • type-1 fuzzy set based applications
  • type-2 fuzzy sets
  • type-2 fuzzy logic systems
  • type-2 fuzzy set based applications.

You will also be exposed to some of the cutting-edge research topics in uncertain data and decision making, e.g., based on type-2 fuzzy logic as well as other fuzzy logic representations. You will develop practical systems and software in a suitable programming language.

Mixed Reality

This module focuses on the possibilities and challenges of interaction beyond the desktop. Exploring the 'mixed reality continuum' - a spectrum of emerging computing applications that runs from virtual reality (in which a user is immersed into a computer-generated virtual world) at one extreme, to ubiquitous computing (in which digital materials appear embedded into the everyday physical world - often referred to as the 'Internet of Things') at the other. In the middle of this continuum lie augmented reality and locative media in which the digital appears to be overlaid upon the physical world in different ways.

You will gain knowledge and hands-on experience of design and development with key technologies along this continuum, including working with both ubiquitous computing based sensor systems and locative media. You will learn about the Human-Computer Interaction challenges that need to be considered when creating mixed reality applications along with strategies for addressing them, so as to create compelling and reliable user experiences.

Simulation and Optimisation for Decision Support

This module offers insight into the applications of selected methods of decision support.

The foundations for applying these methods are derived from:

  • Operations Research Simulation
  • Social Simulation
  • Data Science
  • Automated Scheduling
  • Decision Analysis

Throughout the module, you will become more competent in choosing and implementing the appropriate method for the particular problem at hand. You will spend five hours per week in lectures, workshops, and computer classes for this module.

Programs, Proofs and Types

This module focuses on some of the fundamental mathematical concepts that underlie modern programming and programming languages emphasizing the role of types. We will use a dependently typed programming language/interactive proof system (eg Agda) to implement some concepts on a computer.

Example topics include

  • basic lambda calculus
  • operational semantics
  • domain theory
  • types, propositions as types and formal verification.

You will engage in a mix of lectures and working in the lab with an interactive proof system.

Big Data

This module will cover four main concepts.

It will start with an introduction to big data. You’ll find out about the main principles behind distributed/parallel systems with data intensive applications, identifying key challenges such as capture, store, search, analyse and visualise the data. 

We’ll also look at SQL Databases verses NoSQL Databases. You will learn:

  • the growing amounts of data
  • the relational database management systems (RDBMS)
  • an overview of Structured Query Languages (SQL)
  • an introduction to NoSQL databases
  • the difference between a relational DBMS and a NoSQL database
  • how to identify the need to employ a NoSQL database

Another concept is big data frameworks and how to deal with big data. This includes the MapReduce programming model, as well as an overview of recent technologies (Hadoop ecosystem, and Apache Spark). Then, you will learn how to interact with the latest APIs of Apache Spark (RDDs, DataFrames and Datasets) to create distributed programs capable of dealing with big datasets (using Python and/or Scala).  

Finally, we will cover the data mining and machine learning part of the course. This will include data preprocessing approaches, distributed machine learning algorithms and data stream algorithms. To do so, you will use the machine learning library of Apache Spark to understand how some machine learning algorithms can be deployed at a scale. 

Malware Analysis

This module looks at the practice of malware analysis, looking at how to analyse malicious software to understand how it works, how to identify it, and how to defeat or eliminate it.  

You will look at how to set up a safe environment in which to analyse malware, as well as exploring both static and dynamic malware analysis. Although malware takes many forms, the focus of this module will primarily be on executable binaries. This will cover object file formats and the use of tools such as debuggers, virtual machines, and disassemblers to explore them. Obfuscation and packing schemes will be discussed, along with various issues related to Windows internals.

The module is practical with encouragement to safely practice the skills you're taught.

The above is a sample of the typical modules we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Modules (including methods of assessment) may change or be updated, or modules may be cancelled, over the duration of the course due to a number of reasons such as curriculum developments or staffing changes. Please refer to the module catalogue for information on available modules. This content was last updated on

HackSoc Nottingham

HackSoc is a student-run society that is about building, learning and sharing new tech. Every year they run their own 24-hour hackathon, HackNotts. They also travel to other hackathons to team up with students from around the world.


CompSoc is a student-run society for anyone interested in computer science. They run social events throughout the year such as pizza revision sessions. 

Fees and funding

UK students

Per year

International students

Per year
*For full details including fees for part-time students and reduced fees during your time studying abroad or on placement (where applicable), see our fees page.

If you are a student from the EU, EEA or Switzerland starting your course in the 2022/23 academic year, you will pay international tuition fees.

This does not apply to Irish students, who will be charged tuition fees at the same rate as UK students. UK nationals living in the EU, EEA and Switzerland will also continue to be eligible for ‘home’ fee status at UK universities until 31 December 2027.

For further guidance, check our Brexit information for future students.

Additional costs

As a student on this course, you should factor some additional costs into your budget, alongside your tuition fees and living expenses.

You should be able to access most of the books you’ll need through our libraries, though you may wish to purchase your own copies. If you do these would cost around £40.

Due to our commitment to sustainability, we don’t print lecture notes but these are available digitally. You will be given £5 worth of printer credits a year. You are welcome to buy more credits if you need them. It costs 4p to print one black and white page.

If you study abroad, you need to consider the travel and living costs associated with your country of choice. This may include visa costs and medical insurance. For the year in industry, you may be paid as a full-time employee but you will need to factor in accommodation or travel costs.

Personal laptops are not compulsory as we have computer labs that are open throughout the day but you may want to consider one if you wish to work at home.

Scholarships and bursaries

To help support our students, we offer an Excellence in Computer Science scholarship. There are three levels to the award, which range from 10-50% off your tuition fees. Scholarships are available for the duration of your course, if you meet progression requirements.

Home students*

Over one third of our UK students receive our means-tested core bursary, worth up to £1,000 a year. Full details can be found on our financial support pages.

* A 'home' student is one who meets certain UK residence criteria. These are the same criteria as apply to eligibility for home funding from Student Finance.

International students

We offer a range of international undergraduate scholarships for high-achieving international scholars who can put their Nottingham degree to great use in their careers.

International scholarships


Our graduates are developing the future of computer science. From start-ups to international companies, they are working in roles such as:

  • App Developer
  • Data Analyst 
  • Software Developer
  • Financial Consultant

If research is something that interests you then you could continue studying for a PhD.  

Our graduates have gone on to work in companies such as:

  • BT
  • Capital One
  • Coca-Cola Enterprises
  • Experian
  • Games Workshop
  • Ministry of Defence
  • Sky

Other opportunities to help your employability

The Nottingham Internship Scheme provides a range of work experience opportunities and internships throughout the year. 

The Nottingham Advantage Award is our free scheme to boost your employability. There are over 200 extracurricular activities to choose from.

Average starting salary and career progression

97.6% of undergraduates from the School of Computer Science secured graduate level employment or further study within 15 months of graduation. The average annual salary for these graduates was £33,181.*

* HESA Graduate Outcomes 2020. The Graduate Outcomes % is derived using The Guardian University Guide methodology. The average annual salary is based on graduates working full-time within the UK.

Studying for a degree at the University of Nottingham will provide you with the type of skills and experiences that will prove invaluable in any career, whichever direction you decide to take.

Throughout your time with us, our Careers and Employability Service can work with you to improve your employability skills even further; assisting with job or course applications, searching for appropriate work experience placements and hosting events to bring you closer to a wide range of prospective employers.

Have a look at our careers page for an overview of all the employability support and opportunities that we provide to current students.

The University of Nottingham is consistently named as one of the most targeted universities by Britain’s leading graduate employers (Ranked in the top ten in The Graduate Market in 2013-2020, High Fliers Research).

British Computer Society

Accredited by BCS, The Chartered Institute for IT for the purposes of fully meeting the academic requirement for registration as a Chartered IT Professional. 

Accredited by BCS, The Chartered Institute for IT on behalf of the Engineering Council for the purposes of fully meeting the academic requirement for Incorporated Engineer and partially meeting the academic requirement for a Chartered Engineer.  

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Important information

This online prospectus has been drafted in advance of the academic year to which it applies. Every effort has been made to ensure that the information is accurate at the time of publishing, but changes (for example to course content) are likely to occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for the course where there has been an interval between you reading this website and applying.