
- Computer Science and Artificial Intelligence
BSc (Hons) or MEng — 2026 entry Computer Science and Artificial Intelligence
Artificial intelligence (AI) is transforming industries worldwide, from healthcare and finance to entertainment, transportation and beyond. As this revolution accelerates, expertise in Computer Science and AI has become one of the most in-demand skillsets of the twenty-first century. This programme equips you to be at the forefront of this transformation.
2,832+ people have created a bespoke digital prospectus
Why choose
this course?
You’ll develop advanced competencies in computer science with a focus on large-scale system deployment, as well as in-depth knowledge of emerging technologies in Generative AI, Large Language Models (LLMs), and agentic AI.
Your studies will be enriched by Surrey’s 40 years of internationally acclaimed AI research, guided by world-leading academics who have shaped the future of the field. You’ll also learn from experts in cyber security to make large-scale systems secure and resilient.
Demand for graduates in this field is booming worldwide, offering diverse career opportunities. Surrey has an excellent record for graduate employability: 95 per cent of our computer science undergraduate students go on to employment or further study (Graduate Outcomes 2025, HESA).
Our award-winning Professional Training placements scheme also gives students industry experience and prepares them for roles in various sectors.
Statistics
UK top 10, world top 100
Ranked top 10 in the UK and top 100 in the world for computer science and engineering (ShanghaiRanking Global Ranking of Academic Subjects, 2024)
95%
Of our computer science and electronic engineering graduates are in employment or further study within 15 months of graduating (Graduate Outcomes Survey 2025, HESA)
What you will study
You will study the core principles of computer science in your first year, which is shared with other computer science programmes. In your second year, you’ll then begin to build your specialist AI knowledge, setting you up for an optional placement year. You will then accelerate your learning in AI through the study of the latest developments in AI in your third year of study.
- Learn core computer science principles, concepts necessary for industrial deployment including programming, algorithms, computer security, parallel computing.
- Study advanced AI principles including GenAI, LLMs, computer vision, robotics, medical imaging, intelligent agents, and ethical AI systems.
- Take on hands-on projects using GPU-powered Linux systems, enabling training and deployment of real-world AI models.
- Participate in AI-based group projects with world leading researchers from CVSSP, NICE, and the Surrey Institute for People-Centred AI.
- Use languages and tools such as Java, C++, SQL, Python, and AI libraries.
The structure of our programmes follow clear educational aims that are tailored to each programme. These are all outlined in the programme specifications which include further details such as the learning outcomes.
- Computer Science and Artificial Intelligence BSc (Hons)
- Computer Science and Artificial Intelligence BSc (Hons) with placement
- Computer Science and Artificial Intelligence MEng
- Computer Science and Artificial Intelligence MEng with placement
Please note: The full module listing for the optional Professional Training placement part of your course is available in the relevant programme specification.
Modules
Modules listed are indicative, reflecting the information available at the time of publication. Modules are subject to teaching availability, student demand and/or class size caps.
The University operates a credit framework for all taught programmes based on a 15-credit tariff.
Course options
Year 1 - BSc (Hons)
Semester 1
Compulsory
To introduce the fundamental principles of digital logic, circuits and systems starting with symbolic logic through to the concept of logic gates to the structure and operation of digital logic circuits and systems. This module provides an understanding of the underlying computer architecture and internal operation of computer systems.
View full module detailsThis module aims to introduce students to some of the key concepts of set theory, relations, functions, automata, logic, graphs, trees, proof methods, probability and statistics in order to highlight the importance and power of abstraction within computer science. These concepts are useful throughout the programme.
View full module detailsThis module introduces students to the fundamental concepts of data storage with a focus on relational database systems. Students will learn database design and development to solve real-world problems. The module uses a problem-based approach to provide students with the necessary support to develop their analytical and problem-solving skills.
View full module detailsSemester 2
Compulsory
The course builds upon COM1026, Foundations of Computing, and introduces the key concepts of linear algebra and multivariate calculus.
View full module detailsAppropriate choices of data structures can expedite algorithm efficiency and also aid clear thinking when designing algorithms. It is thus natural for data structures to be studied with algorithms. An algorithm is a sequence of steps for performing some process. A computer program is not an algorithm but a representation of an algorithm. There is a need to be able to create effective algorithms, quantify their efficiency and classify them independently of any computing system or language.
View full module detailsThe module covers the main concepts of modern operating systems (OS). The module has three main parts. The first part of the course provides a short history of operating systems and their purposes. It also introduces the student to multiprocessing and multithreading, i.e. how an OS manages multiple tasks that execute at the same time (concurrently) and share resources. The second part of the course addresses the problem of memory management. The final part of the course introduces file systems and Input/output handling. Throughout the module, case studies of various operating systems are presented with high level concepts that students explore as exercises or deploy their functionality during labs. All taught material is compatible with existing Operating Systems and is suitable to run on a platform such as Linux.
View full module detailsSemester 1 & 2
Compulsory
This module will introduce software engineering principles with a technical focus on Object-Oriented Programming (OOP). Students will explore software development through the lens of the systems development lifecycle. In doing so, experience will be gained in requirements engineering, software design, implementation, testing and how to tackle real-world collaboration. Throughout, software engineering methods will be put into practice, and Java programming skills will be taught. Starting with understanding the basic data types and programming structures, students will progress to more advanced datatypes, programming structuring techniques and key principles of object-oriented programming. The module culminates with a capstone project utilising the software engineering and programming skills taught in the first year.
View full module detailsYear 2 - BSc (Hons)
Semester 1
Compulsory
The module introduces algorithmic techniques for various sets of problems and teaches how to analyse algorithms in terms of their complexity. The techniques build upon the data structures and algorithms module provided in level 4 (COM1029) so that students can further develop their use of methods for solving complex problems. Examples will be used throughout to demonstrate the relevance of each approach.
View full module detailsComputers have become commonplace in many areas of our lives and are able to accomplish many things that humans would find difficult, if not impossible, to do by their own unaided efforts. Whilst computers can perform many calculations in a very short time they generally do not possess the ability to learn or to reason about novel situations or to process incomplete or uncertain data. They will need knowledge of the environment in which they operate so that they can understand what their sensors are monitoring and so that they can behave rationally. This module demonstrates the basic principles and methods of Artificial Intelligence (AI) and provides the basis for understanding and later choosing the correct tools for building such systems. Applications that motivate the development of Artificial Intelligence technology include intelligent robots, automated navigation for autonomous vehicles, object recognition and tracking, medical diagnosis, language communications and many others. Any application that requires human-like intelligence is an application for Artificial Intelligence.
View full module detailsThis module will introduce fundamental concepts of Theory of Programming Languages using two programming paradigms: Object-Oriented Paradigm and the Functional Paradigm. The module will provide a foundation for the theoretical and practical aspects of building programs using these paradigms. Object Orientated Paradigm is first introduced as a popular methodology for large application development. The module will then cover an alternative programming paradigm, Functional Programming, with a focus on both their theoretical underpinnings and computation models. The module will cover practical aspects of implementing algorithms and larger applications in these paradigms.
View full module detailsSemester 2
Compulsory
In recent years, AI has seen tremendous growth due in large part to more powerful computers, larger scale data and techniques to establish comprehensive framework through deeper neural networks. This module introduces a wide range of deep learning and the latest state of art techniques in AI for serving the world through innovation, understanding and compassion. Fundamental concepts on applied maths and establishment on effective learning objectives that thread through key elements in machine learning techniques will be discussed throughout the module. Students will study how to build suitable AI systems that can operate in complicated, real-world environments. The module also prepares students to explore further challenges and opportunities to work with advanced AI and bring them to new frontiers.The module content will typically be updated each year reflecting the latest evolution in AI.
View full module detailsOptional
Expected prior learning: Learning equivalent to Year 1, and Year 2 Semester 1, of EE Programmes. Module purpose: This module provides an introduction to the process of digital image formation in real and computer-generated imagery and builds up EEE1035 Programming in C. Mathematical methods used to represent cameras, scene geometry and lighting in both computer vision and graphics are covered. The course introduces both the theoretical concepts and practical implementation of three-dimensional computer graphics used in visual effects, games, and scientific visualisation. Practical implementation of computer graphics will be introduced using the OpenGL libraries which are widely used in industry. Some of the concepts developed in this module will be useful in other computer vision modules such as EEE3032 Computer Vision and Pattern Recognition.
View full module detailsThe course introduces concepts of parallel and distributed computing by considering different architectures that support this, and working through different categories of examples. The implementation of such solutions and their subsequent analysis gives practical experience and an understanding of the difficulties involved. Special consideration will be given to performance issues of resulting architectures, leading to a foundation for the design of high performance computing for distributed real-time control.
View full module detailsThe understanding of security issues is arguably more important than ever before. This module covers the basic principles behind computer security.
View full module detailsComputer networks are an essential part of almost all corporate computing facilities and even most domestic ones. Interoperability is the key – all components must conform to the same hardware and packet specifications in order that they can be interconnected successfully. This module introduces essential concepts about all the computer networking layering levels with some emphasis on the routing algorithms and implementation of network sensing.
View full module detailsSemester 1 & 2
Compulsory
Software engineering projects are run in teams that must fulfill a variety of roles including project management, background research, design, implementation, quality control and training, whilst also providing sufficient evidence of robust processes to demonstrate compliance with the relevant government and industry standards. This module introduces students to best practices in software engineering and development, as well as technologies for building modern web applications. Students will gain first-hand experience of teamwork through the application of software development and engineering practices by collaboratively designing and delivering a software system using web technologies.In Semester 1, students will develop interactive web applications and learn about the best practices in their design and development. This provides students with an understanding of the core concepts underpinning web applications and provides students with the necessary skills to improve their broader development and problem-solving skills. A practical project-based lab work assessment allows students to demonstrate their proficiency in using and applying frameworks to client- and server-side development as well as use of hosted version control platforms.In Semester 2, teams take ownership of a pre-defined high-level specification and must refine it into a software system which they then implement and test, whilst demonstrating adherence to best software engineering practices. Through this group project, students gain an understanding of how to successfully design a software system that meets the specification, independently research and choose technologies, and implement and evaluate their system before delivering it to clients. Throughout the project, the team is expected to plan and document their activities, hold regular project meetings, and will be evaluated on how they approach the different tasks and adhere to industry standards.
View full module detailsOptional modules for Year 2 - FHEQ Level 5
Students must select 2 options modules out of a choice of 4 optional modules in semester 2
Year 3 - BSc (Hons)
Semester 1
Compulsory
Security is probably the greatest challenge for computer and information system in the near future. Many users have lost data due to viruses, both on home and business computers. Most of us have seen a range of emails massages attempting different kinds of fraud. Vulnerabilities are everywhere. Some are obvious or well-known; others are obscure and harder to spot. Security is not limited to secrecy and confidentiality, but also involves problems like integrity, availability, and effectiveness of information. Moreover, security issues can potentially affect all of us, from innocent home users to companies and even governments.Security is not just a technical problem but needs to be embedded throughout an organisation to be effective. As such good security solutions build on a complete understanding of the values at stake, and the supporting business processes and requirements. This includes people as well as information systems and physical resources. Consequently, raising security awareness and embedding security within roles and policies is as important, if not more, as secure software. In short, secure solutions can only be implemented with both good technical skills and a good understanding of cultures and people skills.
View full module detailsOptional
This module gives an introductory yet up-to-date description of the fundamental technologies of computational Intelligence, including evolutionary computation, neural computing and their applications. Main streams of evolutionary algorithms and meta-heuristics, including genetic algorithms, evolution strategies, genetic programming, particle swarm optimization will be taught. Basic neural network models and learning algorithms will be introduced. Interactions between evolution and learning, real-world applications to optimization and robotics, and recent advances will also be discussed. Good skill in Python programming, good knowledge in mathematics (calculus) are required.
View full module detailsExpected prior learning: Module EEE2041 – Computer Vision & Graphics, or equivalent learning about the geometric interpretation of Linear Algebra (e.g. homogeneous coordinates and matrices for point transformation e.g. rotation, translation, scaling). Module purpose: The module delivers a grounding in Computer Vision, suitable for students with a grounding in linear algebra similar to that provided by EEE2041 – Computer Vision & Graphics) and will help with modules such EEEM071 Advanced Topics in Computer Vision and Deep Learning. Content is presented as an application-focused tour of Computer Vision from the low-level (image processing), through to high level model fitting and object recognition.
View full module detailsThis module introduces general concepts of privacy enhancing technologies and aligns with key concepts recommended by the CyBoK. It will motivate the need for privacy in the modern world and touch on legal considerations, introduce concepts of transparency, control and confidentiality for privacy, and look at privacy preserving and democratic values. This module will also explore how these are realised in a range of applications.
View full module detailsSemester 2
Optional
This module will demonstrate fundamental concepts from the field of Natural Language Processing (NLP) and Computational Linguistics. It will also discuss some of the latest advances in NLP and Generative Artificial Intelligence with a focus on Language Models like BERT, T5, and GPT, and get student up to speed with current research. It will provide the necessary skills to enable students to build computational models for solving a range of problems, such as text classification, sequence classification, machine translation and building conversation agents. The students will learn how to build NLP pipelines for preparing training data and choosing appropriate algorithms and techniques to build such models. The module also focuses on aspects of ethical and trustworthy artificial intelligence with discussion on rigorous model evaluation and ethical considerations for computational modeling. Although traditional linguistic approaches will be mentioned, majority emphasis will be put on the state-of-the-art Deep Learning algorithms and Transfer Learning methods for building efficient and trustworthy NLP solutions.
View full module detailsModule purpose: Modern robotics brings together many aspects of engineering including electronics, hardware, software and AI. This leads to complex asynchronous systems that requires a systems engineering approach. The Robotics Operating System (ROS), is an extensive community built software suite that underpins most leading-edge robotics development. It provides extensive hardware interfacing and high-level functionality which allows complex systems engineering and control while abstracting away much of the complexity inherent to robotics systems design. This module will use ROS to provide a solid foundation in systems engineering based robotics.
View full module detailsExpected prior learning: Module EEE2040 – Communications Networks or equivalent learning. Module purpose: The Internet is an important worldwide communications system; the module provides an in-depth treatment of current and evolving Internet protocols and standards, and the algorithms that underlie them. The module also permits further study on networking in modules such as EEEM018 Advanced Mobile Communication Systems, EEEM023 Network Service management and Control, EEEM032 Advanced Satellite Communication Techniques
View full module detailsMachine/Deep learning has emerged from computer science and artificial intelligence. It draws on methods from a variety of related subjects including statistics, applied mathematics and more specialized fields, such as pattern recognition and neural network computation. This module offers the theory and related applications of advanced deep/machine learning topics and an overview their applications to other fields, such as natural language processing, medical imaging, health, audio, and fintech etc. The deep learning algorithms which will be studied are used widely in industry by AI start-ups to AI tech giants, like, Google, Meta, Microsoft, Amazon, Tesla etc. It provides a background and related theory of deep/machine learning to manipulate data from various domains like image, video, text, audio etc. This is done by various machine learning algorithms that are discussed, implemented, and demonstrated within the module.
View full module detailsThis module explores the major legal and regulatory issues associated with the development and us use of artificial intelligence and other technologies across various sectors, such as financial, healthcare, transportation, and military sectors. Artificial intelligence is considered as a broad discipline with the goal of creating intelligent machines that emulate and then exceed the full range of human cognition.The module will focus on various subsets of AI, such as generative AI, machine learning, unsupervised learning, and their respected legal, regulatory, and ethical challenges based on real case studies and theoretical literature. In addition to AI, the module will explore the legal and regulatory issues associated with the development and use of autonomy, privacy-preserving technologies, blockchain, and quantum computing. Autonomy is defined as the ability of a system to act independently from a human operator.The module will focus on the application of autonomy in various systems, especially in the context of autonomous weapon systems. Further, privacy preserving technologies are newer technologies such as confidential computing, federated learning, synthetic data, or homomorphic encryption that allow to compute on data while preserving fundamental principles of privacy.This module will explore the application of selected privacy-enhancing technologies in various applications, e.g. the use of federated learning in healthcare to collect and commercialise medical data from hospitals or the use of confidential computing for sensitive data sharing across various organisations. Blockchain is a special type of privacy preserving technology based on a decentralized, distributed, and often public, digital ledger which facilitates the process of recording transactions and tracking assets.The module will explore various governance models of blockchain and their legal implications. Finally, quantum technology is a class of technology that works by using the principles of quantum mechanics to gain a functionality or performance which is otherwise unattainable.The module will discuss the role of law and regulation in the current and future development and application of quantum technologies.
View full module detailsSemester 1 & 2
Core
The project consists of a substantial written report and accompanying video presentation and software submission, completed by the student towards the end of their programme of studies. These are based on a major piece of work that involves applying material encountered in the taught component of the degree, and extending that knowledge with the student's contribution, under the guidance of a supervisor. The project lasts over both semesters, and usually involves software development, experimental or theoretical research, or a substantial analysis on a specific topic. Students are also expected to consider the legal, social, ethical and professional aspects of the project.
View full module detailsOptional modules for Year 3 - FHEQ Level 6
Students must select 4 optional modules out of a choice of 8 options modules
Year 1 - BSc (Hons) with placement
Semester 1
Compulsory
To introduce the fundamental principles of digital logic, circuits and systems starting with symbolic logic through to the concept of logic gates to the structure and operation of digital logic circuits and systems. This module provides an understanding of the underlying computer architecture and internal operation of computer systems.
View full module detailsThis module aims to introduce students to some of the key concepts of set theory, relations, functions, automata, logic, graphs, trees, proof methods, probability and statistics in order to highlight the importance and power of abstraction within computer science. These concepts are useful throughout the programme.
View full module detailsThis module introduces students to the fundamental concepts of data storage with a focus on relational database systems. Students will learn database design and development to solve real-world problems. The module uses a problem-based approach to provide students with the necessary support to develop their analytical and problem-solving skills.
View full module detailsSemester 2
Compulsory
The course builds upon COM1026, Foundations of Computing, and introduces the key concepts of linear algebra and multivariate calculus.
View full module detailsAppropriate choices of data structures can expedite algorithm efficiency and also aid clear thinking when designing algorithms. It is thus natural for data structures to be studied with algorithms. An algorithm is a sequence of steps for performing some process. A computer program is not an algorithm but a representation of an algorithm. There is a need to be able to create effective algorithms, quantify their efficiency and classify them independently of any computing system or language.
View full module detailsThe module covers the main concepts of modern operating systems (OS). The module has three main parts. The first part of the course provides a short history of operating systems and their purposes. It also introduces the student to multiprocessing and multithreading, i.e. how an OS manages multiple tasks that execute at the same time (concurrently) and share resources. The second part of the course addresses the problem of memory management. The final part of the course introduces file systems and Input/output handling. Throughout the module, case studies of various operating systems are presented with high level concepts that students explore as exercises or deploy their functionality during labs. All taught material is compatible with existing Operating Systems and is suitable to run on a platform such as Linux.
View full module detailsSemester 1 & 2
Compulsory
This module will introduce software engineering principles with a technical focus on Object-Oriented Programming (OOP). Students will explore software development through the lens of the systems development lifecycle. In doing so, experience will be gained in requirements engineering, software design, implementation, testing and how to tackle real-world collaboration. Throughout, software engineering methods will be put into practice, and Java programming skills will be taught. Starting with understanding the basic data types and programming structures, students will progress to more advanced datatypes, programming structuring techniques and key principles of object-oriented programming. The module culminates with a capstone project utilising the software engineering and programming skills taught in the first year.
View full module detailsYear 2 - BSc (Hons) with placement
Semester 1
Compulsory
The module introduces algorithmic techniques for various sets of problems and teaches how to analyse algorithms in terms of their complexity. The techniques build upon the data structures and algorithms module provided in level 4 (COM1029) so that students can further develop their use of methods for solving complex problems. Examples will be used throughout to demonstrate the relevance of each approach.
View full module detailsComputers have become commonplace in many areas of our lives and are able to accomplish many things that humans would find difficult, if not impossible, to do by their own unaided efforts. Whilst computers can perform many calculations in a very short time they generally do not possess the ability to learn or to reason about novel situations or to process incomplete or uncertain data. They will need knowledge of the environment in which they operate so that they can understand what their sensors are monitoring and so that they can behave rationally. This module demonstrates the basic principles and methods of Artificial Intelligence (AI) and provides the basis for understanding and later choosing the correct tools for building such systems. Applications that motivate the development of Artificial Intelligence technology include intelligent robots, automated navigation for autonomous vehicles, object recognition and tracking, medical diagnosis, language communications and many others. Any application that requires human-like intelligence is an application for Artificial Intelligence.
View full module detailsThis module will introduce fundamental concepts of Theory of Programming Languages using two programming paradigms: Object-Oriented Paradigm and the Functional Paradigm. The module will provide a foundation for the theoretical and practical aspects of building programs using these paradigms. Object Orientated Paradigm is first introduced as a popular methodology for large application development. The module will then cover an alternative programming paradigm, Functional Programming, with a focus on both their theoretical underpinnings and computation models. The module will cover practical aspects of implementing algorithms and larger applications in these paradigms.
View full module detailsSemester 2
Compulsory
In recent years, AI has seen tremendous growth due in large part to more powerful computers, larger scale data and techniques to establish comprehensive framework through deeper neural networks. This module introduces a wide range of deep learning and the latest state of art techniques in AI for serving the world through innovation, understanding and compassion. Fundamental concepts on applied maths and establishment on effective learning objectives that thread through key elements in machine learning techniques will be discussed throughout the module. Students will study how to build suitable AI systems that can operate in complicated, real-world environments. The module also prepares students to explore further challenges and opportunities to work with advanced AI and bring them to new frontiers.The module content will typically be updated each year reflecting the latest evolution in AI.
View full module detailsOptional
Expected prior learning: Learning equivalent to Year 1, and Year 2 Semester 1, of EE Programmes. Module purpose: This module provides an introduction to the process of digital image formation in real and computer-generated imagery and builds up EEE1035 Programming in C. Mathematical methods used to represent cameras, scene geometry and lighting in both computer vision and graphics are covered. The course introduces both the theoretical concepts and practical implementation of three-dimensional computer graphics used in visual effects, games, and scientific visualisation. Practical implementation of computer graphics will be introduced using the OpenGL libraries which are widely used in industry. Some of the concepts developed in this module will be useful in other computer vision modules such as EEE3032 Computer Vision and Pattern Recognition.
View full module detailsThe course introduces concepts of parallel and distributed computing by considering different architectures that support this, and working through different categories of examples. The implementation of such solutions and their subsequent analysis gives practical experience and an understanding of the difficulties involved. Special consideration will be given to performance issues of resulting architectures, leading to a foundation for the design of high performance computing for distributed real-time control.
View full module detailsThe understanding of security issues is arguably more important than ever before. This module covers the basic principles behind computer security.
View full module detailsComputer networks are an essential part of almost all corporate computing facilities and even most domestic ones. Interoperability is the key – all components must conform to the same hardware and packet specifications in order that they can be interconnected successfully. This module introduces essential concepts about all the computer networking layering levels with some emphasis on the routing algorithms and implementation of network sensing.
View full module detailsSemester 1 & 2
Compulsory
Software engineering projects are run in teams that must fulfill a variety of roles including project management, background research, design, implementation, quality control and training, whilst also providing sufficient evidence of robust processes to demonstrate compliance with the relevant government and industry standards. This module introduces students to best practices in software engineering and development, as well as technologies for building modern web applications. Students will gain first-hand experience of teamwork through the application of software development and engineering practices by collaboratively designing and delivering a software system using web technologies.In Semester 1, students will develop interactive web applications and learn about the best practices in their design and development. This provides students with an understanding of the core concepts underpinning web applications and provides students with the necessary skills to improve their broader development and problem-solving skills. A practical project-based lab work assessment allows students to demonstrate their proficiency in using and applying frameworks to client- and server-side development as well as use of hosted version control platforms.In Semester 2, teams take ownership of a pre-defined high-level specification and must refine it into a software system which they then implement and test, whilst demonstrating adherence to best software engineering practices. Through this group project, students gain an understanding of how to successfully design a software system that meets the specification, independently research and choose technologies, and implement and evaluate their system before delivering it to clients. Throughout the project, the team is expected to plan and document their activities, hold regular project meetings, and will be evaluated on how they approach the different tasks and adhere to industry standards.
View full module detailsOptional modules for Year 2 (with PTY) - FHEQ Level 5
Students must select 2 options modules out of a choice of 4 optional modules in semester 2
Year 3 - BSc (Hons) with placement
Semester 1
Compulsory
Security is probably the greatest challenge for computer and information system in the near future. Many users have lost data due to viruses, both on home and business computers. Most of us have seen a range of emails massages attempting different kinds of fraud. Vulnerabilities are everywhere. Some are obvious or well-known; others are obscure and harder to spot. Security is not limited to secrecy and confidentiality, but also involves problems like integrity, availability, and effectiveness of information. Moreover, security issues can potentially affect all of us, from innocent home users to companies and even governments.Security is not just a technical problem but needs to be embedded throughout an organisation to be effective. As such good security solutions build on a complete understanding of the values at stake, and the supporting business processes and requirements. This includes people as well as information systems and physical resources. Consequently, raising security awareness and embedding security within roles and policies is as important, if not more, as secure software. In short, secure solutions can only be implemented with both good technical skills and a good understanding of cultures and people skills.
View full module detailsOptional
This module gives an introductory yet up-to-date description of the fundamental technologies of computational Intelligence, including evolutionary computation, neural computing and their applications. Main streams of evolutionary algorithms and meta-heuristics, including genetic algorithms, evolution strategies, genetic programming, particle swarm optimization will be taught. Basic neural network models and learning algorithms will be introduced. Interactions between evolution and learning, real-world applications to optimization and robotics, and recent advances will also be discussed. Good skill in Python programming, good knowledge in mathematics (calculus) are required.
View full module detailsExpected prior learning: Module EEE2041 – Computer Vision & Graphics, or equivalent learning about the geometric interpretation of Linear Algebra (e.g. homogeneous coordinates and matrices for point transformation e.g. rotation, translation, scaling). Module purpose: The module delivers a grounding in Computer Vision, suitable for students with a grounding in linear algebra similar to that provided by EEE2041 – Computer Vision & Graphics) and will help with modules such EEEM071 Advanced Topics in Computer Vision and Deep Learning. Content is presented as an application-focused tour of Computer Vision from the low-level (image processing), through to high level model fitting and object recognition.
View full module detailsThis module introduces general concepts of privacy enhancing technologies and aligns with key concepts recommended by the CyBoK. It will motivate the need for privacy in the modern world and touch on legal considerations, introduce concepts of transparency, control and confidentiality for privacy, and look at privacy preserving and democratic values. This module will also explore how these are realised in a range of applications.
View full module detailsSemester 2
Optional
This module will demonstrate fundamental concepts from the field of Natural Language Processing (NLP) and Computational Linguistics. It will also discuss some of the latest advances in NLP and Generative Artificial Intelligence with a focus on Language Models like BERT, T5, and GPT, and get student up to speed with current research. It will provide the necessary skills to enable students to build computational models for solving a range of problems, such as text classification, sequence classification, machine translation and building conversation agents. The students will learn how to build NLP pipelines for preparing training data and choosing appropriate algorithms and techniques to build such models. The module also focuses on aspects of ethical and trustworthy artificial intelligence with discussion on rigorous model evaluation and ethical considerations for computational modeling. Although traditional linguistic approaches will be mentioned, majority emphasis will be put on the state-of-the-art Deep Learning algorithms and Transfer Learning methods for building efficient and trustworthy NLP solutions.
View full module detailsModule purpose: Modern robotics brings together many aspects of engineering including electronics, hardware, software and AI. This leads to complex asynchronous systems that requires a systems engineering approach. The Robotics Operating System (ROS), is an extensive community built software suite that underpins most leading-edge robotics development. It provides extensive hardware interfacing and high-level functionality which allows complex systems engineering and control while abstracting away much of the complexity inherent to robotics systems design. This module will use ROS to provide a solid foundation in systems engineering based robotics.
View full module detailsExpected prior learning: Module EEE2040 – Communications Networks or equivalent learning. Module purpose: The Internet is an important worldwide communications system; the module provides an in-depth treatment of current and evolving Internet protocols and standards, and the algorithms that underlie them. The module also permits further study on networking in modules such as EEEM018 Advanced Mobile Communication Systems, EEEM023 Network Service management and Control, EEEM032 Advanced Satellite Communication Techniques
View full module detailsMachine/Deep learning has emerged from computer science and artificial intelligence. It draws on methods from a variety of related subjects including statistics, applied mathematics and more specialized fields, such as pattern recognition and neural network computation. This module offers the theory and related applications of advanced deep/machine learning topics and an overview their applications to other fields, such as natural language processing, medical imaging, health, audio, and fintech etc. The deep learning algorithms which will be studied are used widely in industry by AI start-ups to AI tech giants, like, Google, Meta, Microsoft, Amazon, Tesla etc. It provides a background and related theory of deep/machine learning to manipulate data from various domains like image, video, text, audio etc. This is done by various machine learning algorithms that are discussed, implemented, and demonstrated within the module.
View full module detailsThis module explores the major legal and regulatory issues associated with the development and us use of artificial intelligence and other technologies across various sectors, such as financial, healthcare, transportation, and military sectors. Artificial intelligence is considered as a broad discipline with the goal of creating intelligent machines that emulate and then exceed the full range of human cognition.The module will focus on various subsets of AI, such as generative AI, machine learning, unsupervised learning, and their respected legal, regulatory, and ethical challenges based on real case studies and theoretical literature. In addition to AI, the module will explore the legal and regulatory issues associated with the development and use of autonomy, privacy-preserving technologies, blockchain, and quantum computing. Autonomy is defined as the ability of a system to act independently from a human operator.The module will focus on the application of autonomy in various systems, especially in the context of autonomous weapon systems. Further, privacy preserving technologies are newer technologies such as confidential computing, federated learning, synthetic data, or homomorphic encryption that allow to compute on data while preserving fundamental principles of privacy.This module will explore the application of selected privacy-enhancing technologies in various applications, e.g. the use of federated learning in healthcare to collect and commercialise medical data from hospitals or the use of confidential computing for sensitive data sharing across various organisations. Blockchain is a special type of privacy preserving technology based on a decentralized, distributed, and often public, digital ledger which facilitates the process of recording transactions and tracking assets.The module will explore various governance models of blockchain and their legal implications. Finally, quantum technology is a class of technology that works by using the principles of quantum mechanics to gain a functionality or performance which is otherwise unattainable.The module will discuss the role of law and regulation in the current and future development and application of quantum technologies.
View full module detailsSemester 1 & 2
Core
The project consists of a substantial written report and accompanying video presentation and software submission, completed by the student towards the end of their programme of studies. These are based on a major piece of work that involves applying material encountered in the taught component of the degree, and extending that knowledge with the student's contribution, under the guidance of a supervisor. The project lasts over both semesters, and usually involves software development, experimental or theoretical research, or a substantial analysis on a specific topic. Students are also expected to consider the legal, social, ethical and professional aspects of the project.
View full module detailsOptional modules for Year 3 (with PTY) - FHEQ Level 6
Students must select 4 optional modules out of a choice of 8 options modules
Professional Training Year (PTY)
Semester 1 & 2
Core
This module supports students’ development of personal and professional attitudes and abilities appropriate to a Professional Training placement. It supports and facilitates self-reflection and transfer of learning from their Professional Training placement experiences to their final year of study and their future employment. The PTY module is concerned with Personal and Professional Development towards holistic academic and non-academic learning, and is a process that involves self-reflection, documented via the creation of a personal record, planning and monitoring progress towards the achievement of personal objectives. Development and learning may occur before and during the placement, and this is reflected in the assessment model as a progressive process. However, the graded assessment takes place primarily towards the end of the placement. Additionally, the module aims to enable students to evidence and evaluate their placement experiences and transfer that learning to other situations through written and presentation skills.
View full module detailsThis module supports students' development of personal and professional attitudes and abilities appropriate to a Professional Training placement. It supports and facilitates self-reflection and transfer of learning from their Professional Training placement experiences to their final year of study and their future employment. The PTY module is concerned with Personal and Professional Development towards holistic academic and non-academic learning, and is a process that involves self-reflection, documented via the creation of a personal record, planning and monitoring progress towards the achievement of personal objectives. Development and learning may occur before and during the placement, and this is reflected in the assessment model as a progressive process. However, the graded assessment takes place primarily towards the end of the placement. Additionally, the module aims to enable students to evidence and evaluate their placement experiences and transfer that learning to other situations through written skills.
View full module detailsOptional modules for Professional Training Year (PTY) -
Students must choose COMP009 or COMP010 year-long modules if studying full-time with PTY. Please note PTY year can be offered after Level 5 or Level 6 if doing MEng.
Year 1 - MEng
Semester 1
Compulsory
To introduce the fundamental principles of digital logic, circuits and systems starting with symbolic logic through to the concept of logic gates to the structure and operation of digital logic circuits and systems. This module provides an understanding of the underlying computer architecture and internal operation of computer systems.
View full module detailsThis module aims to introduce students to some of the key concepts of set theory, relations, functions, automata, logic, graphs, trees, proof methods, probability and statistics in order to highlight the importance and power of abstraction within computer science. These concepts are useful throughout the programme.
View full module detailsThis module introduces students to the fundamental concepts of data storage with a focus on relational database systems. Students will learn database design and development to solve real-world problems. The module uses a problem-based approach to provide students with the necessary support to develop their analytical and problem-solving skills.
View full module detailsSemester 2
Compulsory
The course builds upon COM1026, Foundations of Computing, and introduces the key concepts of linear algebra and multivariate calculus.
View full module detailsAppropriate choices of data structures can expedite algorithm efficiency and also aid clear thinking when designing algorithms. It is thus natural for data structures to be studied with algorithms. An algorithm is a sequence of steps for performing some process. A computer program is not an algorithm but a representation of an algorithm. There is a need to be able to create effective algorithms, quantify their efficiency and classify them independently of any computing system or language.
View full module detailsThe module covers the main concepts of modern operating systems (OS). The module has three main parts. The first part of the course provides a short history of operating systems and their purposes. It also introduces the student to multiprocessing and multithreading, i.e. how an OS manages multiple tasks that execute at the same time (concurrently) and share resources. The second part of the course addresses the problem of memory management. The final part of the course introduces file systems and Input/output handling. Throughout the module, case studies of various operating systems are presented with high level concepts that students explore as exercises or deploy their functionality during labs. All taught material is compatible with existing Operating Systems and is suitable to run on a platform such as Linux.
View full module detailsSemester 1 & 2
Compulsory
This module will introduce software engineering principles with a technical focus on Object-Oriented Programming (OOP). Students will explore software development through the lens of the systems development lifecycle. In doing so, experience will be gained in requirements engineering, software design, implementation, testing and how to tackle real-world collaboration. Throughout, software engineering methods will be put into practice, and Java programming skills will be taught. Starting with understanding the basic data types and programming structures, students will progress to more advanced datatypes, programming structuring techniques and key principles of object-oriented programming. The module culminates with a capstone project utilising the software engineering and programming skills taught in the first year.
View full module detailsYear 2 - MEng
Semester 1
Compulsory
The module introduces algorithmic techniques for various sets of problems and teaches how to analyse algorithms in terms of their complexity. The techniques build upon the data structures and algorithms module provided in level 4 (COM1029) so that students can further develop their use of methods for solving complex problems. Examples will be used throughout to demonstrate the relevance of each approach.
View full module detailsComputers have become commonplace in many areas of our lives and are able to accomplish many things that humans would find difficult, if not impossible, to do by their own unaided efforts. Whilst computers can perform many calculations in a very short time they generally do not possess the ability to learn or to reason about novel situations or to process incomplete or uncertain data. They will need knowledge of the environment in which they operate so that they can understand what their sensors are monitoring and so that they can behave rationally. This module demonstrates the basic principles and methods of Artificial Intelligence (AI) and provides the basis for understanding and later choosing the correct tools for building such systems. Applications that motivate the development of Artificial Intelligence technology include intelligent robots, automated navigation for autonomous vehicles, object recognition and tracking, medical diagnosis, language communications and many others. Any application that requires human-like intelligence is an application for Artificial Intelligence.
View full module detailsThis module will introduce fundamental concepts of Theory of Programming Languages using two programming paradigms: Object-Oriented Paradigm and the Functional Paradigm. The module will provide a foundation for the theoretical and practical aspects of building programs using these paradigms. Object Orientated Paradigm is first introduced as a popular methodology for large application development. The module will then cover an alternative programming paradigm, Functional Programming, with a focus on both their theoretical underpinnings and computation models. The module will cover practical aspects of implementing algorithms and larger applications in these paradigms.
View full module detailsSemester 2
Compulsory
In recent years, AI has seen tremendous growth due in large part to more powerful computers, larger scale data and techniques to establish comprehensive framework through deeper neural networks. This module introduces a wide range of deep learning and the latest state of art techniques in AI for serving the world through innovation, understanding and compassion. Fundamental concepts on applied maths and establishment on effective learning objectives that thread through key elements in machine learning techniques will be discussed throughout the module. Students will study how to build suitable AI systems that can operate in complicated, real-world environments. The module also prepares students to explore further challenges and opportunities to work with advanced AI and bring them to new frontiers.The module content will typically be updated each year reflecting the latest evolution in AI.
View full module detailsOptional
Computer networks are an essential part of almost all corporate computing facilities and even most domestic ones. Interoperability is the key – all components must conform to the same hardware and packet specifications in order that they can be interconnected successfully. This module introduces essential concepts about all the computer networking layering levels with some emphasis on the routing algorithms and implementation of network sensing.
View full module detailsExpected prior learning: Learning equivalent to Year 1, and Year 2 Semester 1, of EE Programmes. Module purpose: This module provides an introduction to the process of digital image formation in real and computer-generated imagery and builds up EEE1035 Programming in C. Mathematical methods used to represent cameras, scene geometry and lighting in both computer vision and graphics are covered. The course introduces both the theoretical concepts and practical implementation of three-dimensional computer graphics used in visual effects, games, and scientific visualisation. Practical implementation of computer graphics will be introduced using the OpenGL libraries which are widely used in industry. Some of the concepts developed in this module will be useful in other computer vision modules such as EEE3032 Computer Vision and Pattern Recognition.
View full module detailsThe course introduces concepts of parallel and distributed computing by considering different architectures that support this, and working through different categories of examples. The implementation of such solutions and their subsequent analysis gives practical experience and an understanding of the difficulties involved. Special consideration will be given to performance issues of resulting architectures, leading to a foundation for the design of high performance computing for distributed real-time control.
View full module detailsThe understanding of security issues is arguably more important than ever before. This module covers the basic principles behind computer security.
View full module detailsSemester 1 & 2
Compulsory
Software engineering projects are run in teams that must fulfill a variety of roles including project management, background research, design, implementation, quality control and training, whilst also providing sufficient evidence of robust processes to demonstrate compliance with the relevant government and industry standards. This module introduces students to best practices in software engineering and development, as well as technologies for building modern web applications. Students will gain first-hand experience of teamwork through the application of software development and engineering practices by collaboratively designing and delivering a software system using web technologies.In Semester 1, students will develop interactive web applications and learn about the best practices in their design and development. This provides students with an understanding of the core concepts underpinning web applications and provides students with the necessary skills to improve their broader development and problem-solving skills. A practical project-based lab work assessment allows students to demonstrate their proficiency in using and applying frameworks to client- and server-side development as well as use of hosted version control platforms.In Semester 2, teams take ownership of a pre-defined high-level specification and must refine it into a software system which they then implement and test, whilst demonstrating adherence to best software engineering practices. Through this group project, students gain an understanding of how to successfully design a software system that meets the specification, independently research and choose technologies, and implement and evaluate their system before delivering it to clients. Throughout the project, the team is expected to plan and document their activities, hold regular project meetings, and will be evaluated on how they approach the different tasks and adhere to industry standards.
View full module detailsOptional modules for Year 2 - FHEQ Level 5
Students select 2 optional modules out of a choice of 4 optional modules in semester 2
Year 3 - MEng
Semester 1
Compulsory
Security is probably the greatest challenge for computer and information system in the near future. Many users have lost data due to viruses, both on home and business computers. Most of us have seen a range of emails massages attempting different kinds of fraud. Vulnerabilities are everywhere. Some are obvious or well-known; others are obscure and harder to spot. Security is not limited to secrecy and confidentiality, but also involves problems like integrity, availability, and effectiveness of information. Moreover, security issues can potentially affect all of us, from innocent home users to companies and even governments.Security is not just a technical problem but needs to be embedded throughout an organisation to be effective. As such good security solutions build on a complete understanding of the values at stake, and the supporting business processes and requirements. This includes people as well as information systems and physical resources. Consequently, raising security awareness and embedding security within roles and policies is as important, if not more, as secure software. In short, secure solutions can only be implemented with both good technical skills and a good understanding of cultures and people skills.
View full module detailsOptional
This module gives an introductory yet up-to-date description of the fundamental technologies of computational Intelligence, including evolutionary computation, neural computing and their applications. Main streams of evolutionary algorithms and meta-heuristics, including genetic algorithms, evolution strategies, genetic programming, particle swarm optimization will be taught. Basic neural network models and learning algorithms will be introduced. Interactions between evolution and learning, real-world applications to optimization and robotics, and recent advances will also be discussed. Good skill in Python programming, good knowledge in mathematics (calculus) are required.
View full module detailsExpected prior learning: Module EEE2041 – Computer Vision & Graphics, or equivalent learning about the geometric interpretation of Linear Algebra (e.g. homogeneous coordinates and matrices for point transformation e.g. rotation, translation, scaling). Module purpose: The module delivers a grounding in Computer Vision, suitable for students with a grounding in linear algebra similar to that provided by EEE2041 – Computer Vision & Graphics) and will help with modules such EEEM071 Advanced Topics in Computer Vision and Deep Learning. Content is presented as an application-focused tour of Computer Vision from the low-level (image processing), through to high level model fitting and object recognition.
View full module detailsThis module introduces general concepts of privacy enhancing technologies and aligns with key concepts recommended by the CyBoK. It will motivate the need for privacy in the modern world and touch on legal considerations, introduce concepts of transparency, control and confidentiality for privacy, and look at privacy preserving and democratic values. This module will also explore how these are realised in a range of applications.
View full module detailsSemester 2
Optional
This module will demonstrate fundamental concepts from the field of Natural Language Processing (NLP) and Computational Linguistics. It will also discuss some of the latest advances in NLP and Generative Artificial Intelligence with a focus on Language Models like BERT, T5, and GPT, and get student up to speed with current research. It will provide the necessary skills to enable students to build computational models for solving a range of problems, such as text classification, sequence classification, machine translation and building conversation agents. The students will learn how to build NLP pipelines for preparing training data and choosing appropriate algorithms and techniques to build such models. The module also focuses on aspects of ethical and trustworthy artificial intelligence with discussion on rigorous model evaluation and ethical considerations for computational modeling. Although traditional linguistic approaches will be mentioned, majority emphasis will be put on the state-of-the-art Deep Learning algorithms and Transfer Learning methods for building efficient and trustworthy NLP solutions.
View full module detailsModule purpose: Modern robotics brings together many aspects of engineering including electronics, hardware, software and AI. This leads to complex asynchronous systems that requires a systems engineering approach. The Robotics Operating System (ROS), is an extensive community built software suite that underpins most leading-edge robotics development. It provides extensive hardware interfacing and high-level functionality which allows complex systems engineering and control while abstracting away much of the complexity inherent to robotics systems design. This module will use ROS to provide a solid foundation in systems engineering based robotics.
View full module detailsExpected prior learning: Module EEE2040 – Communications Networks or equivalent learning. Module purpose: The Internet is an important worldwide communications system; the module provides an in-depth treatment of current and evolving Internet protocols and standards, and the algorithms that underlie them. The module also permits further study on networking in modules such as EEEM018 Advanced Mobile Communication Systems, EEEM023 Network Service management and Control, EEEM032 Advanced Satellite Communication Techniques
View full module detailsMachine/Deep learning has emerged from computer science and artificial intelligence. It draws on methods from a variety of related subjects including statistics, applied mathematics and more specialized fields, such as pattern recognition and neural network computation. This module offers the theory and related applications of advanced deep/machine learning topics and an overview their applications to other fields, such as natural language processing, medical imaging, health, audio, and fintech etc. The deep learning algorithms which will be studied are used widely in industry by AI start-ups to AI tech giants, like, Google, Meta, Microsoft, Amazon, Tesla etc. It provides a background and related theory of deep/machine learning to manipulate data from various domains like image, video, text, audio etc. This is done by various machine learning algorithms that are discussed, implemented, and demonstrated within the module.
View full module detailsThis module explores the major legal and regulatory issues associated with the development and us use of artificial intelligence and other technologies across various sectors, such as financial, healthcare, transportation, and military sectors. Artificial intelligence is considered as a broad discipline with the goal of creating intelligent machines that emulate and then exceed the full range of human cognition.The module will focus on various subsets of AI, such as generative AI, machine learning, unsupervised learning, and their respected legal, regulatory, and ethical challenges based on real case studies and theoretical literature. In addition to AI, the module will explore the legal and regulatory issues associated with the development and use of autonomy, privacy-preserving technologies, blockchain, and quantum computing. Autonomy is defined as the ability of a system to act independently from a human operator.The module will focus on the application of autonomy in various systems, especially in the context of autonomous weapon systems. Further, privacy preserving technologies are newer technologies such as confidential computing, federated learning, synthetic data, or homomorphic encryption that allow to compute on data while preserving fundamental principles of privacy.This module will explore the application of selected privacy-enhancing technologies in various applications, e.g. the use of federated learning in healthcare to collect and commercialise medical data from hospitals or the use of confidential computing for sensitive data sharing across various organisations. Blockchain is a special type of privacy preserving technology based on a decentralized, distributed, and often public, digital ledger which facilitates the process of recording transactions and tracking assets.The module will explore various governance models of blockchain and their legal implications. Finally, quantum technology is a class of technology that works by using the principles of quantum mechanics to gain a functionality or performance which is otherwise unattainable.The module will discuss the role of law and regulation in the current and future development and application of quantum technologies.
View full module detailsSemester 1 & 2
Core
The project consists of a substantial written report and accompanying video presentation and software submission, completed by the student towards the end of their programme of studies. These are based on a major piece of work that involves applying material encountered in the taught component of the degree, and extending that knowledge with the student's contribution, under the guidance of a supervisor. The project lasts over both semesters, and usually involves software development, experimental or theoretical research, or a substantial analysis on a specific topic. Students are also expected to consider the legal, social, ethical and professional aspects of the project.
View full module detailsOptional modules for Year 3 - FHEQ Level 6
Students must select 4 optional modules out of a choice of 8 optional modules
Year 4 - MEng
Semester 1
Compulsory
Module purpose: This module was conceived to answer the SARTOR 3 requirement that each MEng student participates in a multi-disciplinary design activity. It involves students from Aerospace, Civil, Chemical, Electronic, Mechanical and Medical Engineering working in groups which contain at least 3, and often 4, disciplines. The projects are conceived by Royal Academy of Engineering (RAE) Visiting Professors from Industry (who enjoy the active support of their sponsoring organisation). It aims to emulate an intensive Industrial Design Project.
View full module detailsOptional
This module will introduce and explore the underlying concepts and technologies of virtual/augmented reality (VR/AR) and the emerging idea of the Metaverse. The module will also investigate the current and future challenges of the technologies and consider the impact it will have on industry and wider society.
View full module detailsMedical robotics is a rapidly developing industry that is vital to healthcare systems seeking better outcomes at reduced overall cost. This module introduces students to the workings of robots and how this is applied in solving both surgical and broader healthcare challenges. Students learn through lectures, practical sessions, tutorials and seminars requiring engagement with scientific literature. Case studies are a critical part of the module. These are industrially or research-based and require students to think about clinical conditions, ethical considerations and a range of attitudes to healthcare.The unit of assessment requires students to develop an understanding of the general theory behind robotics and identify the particularities applying to medical robots. The unit of assessment will also address the wider issues associated with medical robotics and their application. Practical sessions enable students to work with each other to solve problems and demonstrate the theoretical components of the module. An overarching series of lectures delivers critical technical information and links students¿ learning with case-studies to illustrate mechanical and medical issues. Seminars complement lectures and are designed for students to critically analyse, discuss and focus on particular aspects of medical robotic research in the scientific literature.
View full module detailsModule purpose: Advances related to energy efficiency issues and cost reductions have resulted in the rapid growth and deployment of networked devices and sensing/actuation systems that connect the physical world with the cyber world. This evolving framework, now recognized as the Artificial Intelligence of Things (AIoT), integrates IoT technologies with artificial intelligence (AI) to enhance automation, intelligence, and decision-making. AIoT incorporates several cutting-edge technologies, including wireless sensor networks, pervasive systems, ambient intelligence, context awareness, distributed systems, and machine learning-driven analytics. Module Overview: The advanced AIoT module is designed to provide a comprehensive understanding of how machine communications , coupled with AI, contribute to creating smart artificial intelligence-driven environments, focusing on networking and communication systems. The module provides an overview of the key concepts and enabling technologies for AIoT. It encompasses a cross-layer approach, allowing students to explore the practical aspects of sensors, actuators, and mainly communication systems for AIoT across physical, media access, and network layers. This includes security considerations, satellite AIoT, positioning and tracking for industrial applications, AIoT Platforms (Hardware, Software), protocols and standards (e.g. 6LowPAN, ZigBee, CoAp), semantic technologies, and data and information processing mechanisms. Also, the module explores AI-driven methodologies such as ensemble learning, multi-armed bandits for sequential decision-making, and lightweight machine learning Mmodels for AIoT applications. These techniques enhance real-time data analysis, predictive maintenance, anomaly detection, and adaptive control while ensuring computational efficiency.
View full module detailsThis module offers an introduction to the use of AI in society, work, media and communication, government and policy. It puts people ¿ as opposed to technology -- in the centre of AI, and highlights core considerations in planning for AI applications as a response to issues and considerations in the society. This is done by exploring varied positions of users and stakeholders in relation to AI, examining the suitability of AI and associated tools and methods to the productivity/progress/propagation in society. In this module we discuss the opportunities, but also the challenges, risks, threats and ethical implications involved in the use of AI in society.
View full module detailsSemester 2
Compulsory
Module purpose: This course offers an introduction to image processing and computer vision for those interested in the science and technology of machine vision. It provides background and the theory for building artificial systems that manipulate videos and images and alter or analyse their information content. This is done by various computer algorithms that are discussed, implemented and demonstrated.
View full module detailsOptional
The need for computational power and data storage continues to drive demand for more highly capable systems. Highly data intensive applications demand fast access to terabytes, petabytes, even exabytes of storage; processor intensive applications demand access to various types of processors in various configurations. Such applications are increasingly being developed in both scientific and industrial contexts and need to be variously scalable and supportable for large numbers of geographically distributed users. This module will provide insights into how Cloud Computing attempts to meet the varying needs of such applications.
View full module detailsThe module provides an application-focused tour of machine learning for real-world healthcare research and application from understanding various healthcare components, ethical concerns to pre-processing and analysing healthcare data for classification, survival and risk analysis, and early prediction tasks. The module requires and builds on the knowledge of basic machine learning, linear algebra, and familiarity with Python programming. Labs are designed to support understanding of the theory and enable development of practical skills required for future employability.
View full module detailsRecently, Artificial Intelligence (AI) has been playing a key role in the research and development of scientific and technological breakthroughs in many disciplines to solve real world problems, providing new foundations and steppingstones to foster more advances and solutions. In this context, AI has a great potential to play a transformative role in helping to achieve the United Nations Sustainable Development Goals (UNSDG), by providing new insights, enabling more efficient use of resources, and supporting a better understanding of complex systems that underpin the dynamics of people's lives and the planet's environment. Therefore, the purpose of this module is to present the key concepts with practical applications related to the development of more sustainable AI techniques (e.g. model, data and energy efficiency, bias and unfairness identification and mitigation, trustworthy AI, physics-informed neural networks etc.), and AI solutions to support UNSDGs (e.g. clean air, clean energy, clean water, waste management, smart manufacturing etc.).
View full module detailsThe module introduces general information and network security principles, challenges and goals and then focuses on main security mechanisms and protocols for protecting network communication across different layers of the Internet protocol stack. This will include discussion on various attacks on the networks, penetration testing tools and possible countermeasures to ensure protection of authentication, confidentiality and end-to-end security of communications. In labs students will be able to practice experience with various network security protocols and tools.
View full module detailsThe main application of machine learning is out-of-sample prediction. Prediction accuracy is typically evaluated in terms of squared error, where the error is difference between the prediction and the actual realization. In certain situations, such as forecasts of inflation or output from the Bank of England, an accurate prediction is enough. However, there are situations, like policy evaluation, in which we care about causal effects. Suppose that the Secretary of Education introduces three additional hours of mathematics in primary school to increase student GSE scores. Here the objective is to isolate the effect of additional hours of math on GSE score. In general, for each pupil, we have a lot of individual characteristics, which we need to control for. Data reduction techniques, such as LASSO, regression tree, random forest, help to eliminate all irrelevant information so that we can isolate the effect of the policy. This module is structured in two parts. In the first part, we review econometric tools for policy evaluation, such as instrumental variables, panel data, difference-in-difference, synthetic control, regression discontinuity. In the second part, we look at the same techniques when many instruments are available or many additional control variables are available.
View full module detailsOptional modules for Year 4 - FHEQ Level 7
Students may undertake up to 5 optional modules out of a choice of 9 optional modules. Select 2 optional modules in semester 1; Only 2 options in total from (EEEMO86, COMM068, COMM034) can be selected.
Year 1 - MEng with placement
Semester 1
Compulsory
To introduce the fundamental principles of digital logic, circuits and systems starting with symbolic logic through to the concept of logic gates to the structure and operation of digital logic circuits and systems. This module provides an understanding of the underlying computer architecture and internal operation of computer systems.
View full module detailsThis module aims to introduce students to some of the key concepts of set theory, relations, functions, automata, logic, graphs, trees, proof methods, probability and statistics in order to highlight the importance and power of abstraction within computer science. These concepts are useful throughout the programme.
View full module detailsThis module introduces students to the fundamental concepts of data storage with a focus on relational database systems. Students will learn database design and development to solve real-world problems. The module uses a problem-based approach to provide students with the necessary support to develop their analytical and problem-solving skills.
View full module detailsSemester 2
Compulsory
The course builds upon COM1026, Foundations of Computing, and introduces the key concepts of linear algebra and multivariate calculus.
View full module detailsAppropriate choices of data structures can expedite algorithm efficiency and also aid clear thinking when designing algorithms. It is thus natural for data structures to be studied with algorithms. An algorithm is a sequence of steps for performing some process. A computer program is not an algorithm but a representation of an algorithm. There is a need to be able to create effective algorithms, quantify their efficiency and classify them independently of any computing system or language.
View full module detailsThe module covers the main concepts of modern operating systems (OS). The module has three main parts. The first part of the course provides a short history of operating systems and their purposes. It also introduces the student to multiprocessing and multithreading, i.e. how an OS manages multiple tasks that execute at the same time (concurrently) and share resources. The second part of the course addresses the problem of memory management. The final part of the course introduces file systems and Input/output handling. Throughout the module, case studies of various operating systems are presented with high level concepts that students explore as exercises or deploy their functionality during labs. All taught material is compatible with existing Operating Systems and is suitable to run on a platform such as Linux.
View full module detailsSemester 1 & 2
Compulsory
This module will introduce software engineering principles with a technical focus on Object-Oriented Programming (OOP). Students will explore software development through the lens of the systems development lifecycle. In doing so, experience will be gained in requirements engineering, software design, implementation, testing and how to tackle real-world collaboration. Throughout, software engineering methods will be put into practice, and Java programming skills will be taught. Starting with understanding the basic data types and programming structures, students will progress to more advanced datatypes, programming structuring techniques and key principles of object-oriented programming. The module culminates with a capstone project utilising the software engineering and programming skills taught in the first year.
View full module detailsYear 2 - MEng with placement
Semester 1
Compulsory
The module introduces algorithmic techniques for various sets of problems and teaches how to analyse algorithms in terms of their complexity. The techniques build upon the data structures and algorithms module provided in level 4 (COM1029) so that students can further develop their use of methods for solving complex problems. Examples will be used throughout to demonstrate the relevance of each approach.
View full module detailsComputers have become commonplace in many areas of our lives and are able to accomplish many things that humans would find difficult, if not impossible, to do by their own unaided efforts. Whilst computers can perform many calculations in a very short time they generally do not possess the ability to learn or to reason about novel situations or to process incomplete or uncertain data. They will need knowledge of the environment in which they operate so that they can understand what their sensors are monitoring and so that they can behave rationally. This module demonstrates the basic principles and methods of Artificial Intelligence (AI) and provides the basis for understanding and later choosing the correct tools for building such systems. Applications that motivate the development of Artificial Intelligence technology include intelligent robots, automated navigation for autonomous vehicles, object recognition and tracking, medical diagnosis, language communications and many others. Any application that requires human-like intelligence is an application for Artificial Intelligence.
View full module detailsThis module will introduce fundamental concepts of Theory of Programming Languages using two programming paradigms: Object-Oriented Paradigm and the Functional Paradigm. The module will provide a foundation for the theoretical and practical aspects of building programs using these paradigms. Object Orientated Paradigm is first introduced as a popular methodology for large application development. The module will then cover an alternative programming paradigm, Functional Programming, with a focus on both their theoretical underpinnings and computation models. The module will cover practical aspects of implementing algorithms and larger applications in these paradigms.
View full module detailsSemester 2
Compulsory
In recent years, AI has seen tremendous growth due in large part to more powerful computers, larger scale data and techniques to establish comprehensive framework through deeper neural networks. This module introduces a wide range of deep learning and the latest state of art techniques in AI for serving the world through innovation, understanding and compassion. Fundamental concepts on applied maths and establishment on effective learning objectives that thread through key elements in machine learning techniques will be discussed throughout the module. Students will study how to build suitable AI systems that can operate in complicated, real-world environments. The module also prepares students to explore further challenges and opportunities to work with advanced AI and bring them to new frontiers.The module content will typically be updated each year reflecting the latest evolution in AI.
View full module detailsOptional
Computer networks are an essential part of almost all corporate computing facilities and even most domestic ones. Interoperability is the key – all components must conform to the same hardware and packet specifications in order that they can be interconnected successfully. This module introduces essential concepts about all the computer networking layering levels with some emphasis on the routing algorithms and implementation of network sensing.
View full module detailsExpected prior learning: Learning equivalent to Year 1, and Year 2 Semester 1, of EE Programmes. Module purpose: This module provides an introduction to the process of digital image formation in real and computer-generated imagery and builds up EEE1035 Programming in C. Mathematical methods used to represent cameras, scene geometry and lighting in both computer vision and graphics are covered. The course introduces both the theoretical concepts and practical implementation of three-dimensional computer graphics used in visual effects, games, and scientific visualisation. Practical implementation of computer graphics will be introduced using the OpenGL libraries which are widely used in industry. Some of the concepts developed in this module will be useful in other computer vision modules such as EEE3032 Computer Vision and Pattern Recognition.
View full module detailsThe course introduces concepts of parallel and distributed computing by considering different architectures that support this, and working through different categories of examples. The implementation of such solutions and their subsequent analysis gives practical experience and an understanding of the difficulties involved. Special consideration will be given to performance issues of resulting architectures, leading to a foundation for the design of high performance computing for distributed real-time control.
View full module detailsThe understanding of security issues is arguably more important than ever before. This module covers the basic principles behind computer security.
View full module detailsSemester 1 & 2
Compulsory
Software engineering projects are run in teams that must fulfill a variety of roles including project management, background research, design, implementation, quality control and training, whilst also providing sufficient evidence of robust processes to demonstrate compliance with the relevant government and industry standards. This module introduces students to best practices in software engineering and development, as well as technologies for building modern web applications. Students will gain first-hand experience of teamwork through the application of software development and engineering practices by collaboratively designing and delivering a software system using web technologies.In Semester 1, students will develop interactive web applications and learn about the best practices in their design and development. This provides students with an understanding of the core concepts underpinning web applications and provides students with the necessary skills to improve their broader development and problem-solving skills. A practical project-based lab work assessment allows students to demonstrate their proficiency in using and applying frameworks to client- and server-side development as well as use of hosted version control platforms.In Semester 2, teams take ownership of a pre-defined high-level specification and must refine it into a software system which they then implement and test, whilst demonstrating adherence to best software engineering practices. Through this group project, students gain an understanding of how to successfully design a software system that meets the specification, independently research and choose technologies, and implement and evaluate their system before delivering it to clients. Throughout the project, the team is expected to plan and document their activities, hold regular project meetings, and will be evaluated on how they approach the different tasks and adhere to industry standards.
View full module detailsOptional modules for Year 2 (with PTY) - FHEQ Level 5
Students select 2 optional modules out of a choice of 4 optional modules in semester 2
Year 3 - MEng with placement
Semester 1
Compulsory
Security is probably the greatest challenge for computer and information system in the near future. Many users have lost data due to viruses, both on home and business computers. Most of us have seen a range of emails massages attempting different kinds of fraud. Vulnerabilities are everywhere. Some are obvious or well-known; others are obscure and harder to spot. Security is not limited to secrecy and confidentiality, but also involves problems like integrity, availability, and effectiveness of information. Moreover, security issues can potentially affect all of us, from innocent home users to companies and even governments.Security is not just a technical problem but needs to be embedded throughout an organisation to be effective. As such good security solutions build on a complete understanding of the values at stake, and the supporting business processes and requirements. This includes people as well as information systems and physical resources. Consequently, raising security awareness and embedding security within roles and policies is as important, if not more, as secure software. In short, secure solutions can only be implemented with both good technical skills and a good understanding of cultures and people skills.
View full module detailsOptional
This module gives an introductory yet up-to-date description of the fundamental technologies of computational Intelligence, including evolutionary computation, neural computing and their applications. Main streams of evolutionary algorithms and meta-heuristics, including genetic algorithms, evolution strategies, genetic programming, particle swarm optimization will be taught. Basic neural network models and learning algorithms will be introduced. Interactions between evolution and learning, real-world applications to optimization and robotics, and recent advances will also be discussed. Good skill in Python programming, good knowledge in mathematics (calculus) are required.
View full module detailsExpected prior learning: Module EEE2041 – Computer Vision & Graphics, or equivalent learning about the geometric interpretation of Linear Algebra (e.g. homogeneous coordinates and matrices for point transformation e.g. rotation, translation, scaling). Module purpose: The module delivers a grounding in Computer Vision, suitable for students with a grounding in linear algebra similar to that provided by EEE2041 – Computer Vision & Graphics) and will help with modules such EEEM071 Advanced Topics in Computer Vision and Deep Learning. Content is presented as an application-focused tour of Computer Vision from the low-level (image processing), through to high level model fitting and object recognition.
View full module detailsThis module introduces general concepts of privacy enhancing technologies and aligns with key concepts recommended by the CyBoK. It will motivate the need for privacy in the modern world and touch on legal considerations, introduce concepts of transparency, control and confidentiality for privacy, and look at privacy preserving and democratic values. This module will also explore how these are realised in a range of applications.
View full module detailsSemester 2
Optional
This module will demonstrate fundamental concepts from the field of Natural Language Processing (NLP) and Computational Linguistics. It will also discuss some of the latest advances in NLP and Generative Artificial Intelligence with a focus on Language Models like BERT, T5, and GPT, and get student up to speed with current research. It will provide the necessary skills to enable students to build computational models for solving a range of problems, such as text classification, sequence classification, machine translation and building conversation agents. The students will learn how to build NLP pipelines for preparing training data and choosing appropriate algorithms and techniques to build such models. The module also focuses on aspects of ethical and trustworthy artificial intelligence with discussion on rigorous model evaluation and ethical considerations for computational modeling. Although traditional linguistic approaches will be mentioned, majority emphasis will be put on the state-of-the-art Deep Learning algorithms and Transfer Learning methods for building efficient and trustworthy NLP solutions.
View full module detailsModule purpose: Modern robotics brings together many aspects of engineering including electronics, hardware, software and AI. This leads to complex asynchronous systems that requires a systems engineering approach. The Robotics Operating System (ROS), is an extensive community built software suite that underpins most leading-edge robotics development. It provides extensive hardware interfacing and high-level functionality which allows complex systems engineering and control while abstracting away much of the complexity inherent to robotics systems design. This module will use ROS to provide a solid foundation in systems engineering based robotics.
View full module detailsExpected prior learning: Module EEE2040 – Communications Networks or equivalent learning. Module purpose: The Internet is an important worldwide communications system; the module provides an in-depth treatment of current and evolving Internet protocols and standards, and the algorithms that underlie them. The module also permits further study on networking in modules such as EEEM018 Advanced Mobile Communication Systems, EEEM023 Network Service management and Control, EEEM032 Advanced Satellite Communication Techniques
View full module detailsMachine/Deep learning has emerged from computer science and artificial intelligence. It draws on methods from a variety of related subjects including statistics, applied mathematics and more specialized fields, such as pattern recognition and neural network computation. This module offers the theory and related applications of advanced deep/machine learning topics and an overview their applications to other fields, such as natural language processing, medical imaging, health, audio, and fintech etc. The deep learning algorithms which will be studied are used widely in industry by AI start-ups to AI tech giants, like, Google, Meta, Microsoft, Amazon, Tesla etc. It provides a background and related theory of deep/machine learning to manipulate data from various domains like image, video, text, audio etc. This is done by various machine learning algorithms that are discussed, implemented, and demonstrated within the module.
View full module detailsThis module explores the major legal and regulatory issues associated with the development and us use of artificial intelligence and other technologies across various sectors, such as financial, healthcare, transportation, and military sectors. Artificial intelligence is considered as a broad discipline with the goal of creating intelligent machines that emulate and then exceed the full range of human cognition.The module will focus on various subsets of AI, such as generative AI, machine learning, unsupervised learning, and their respected legal, regulatory, and ethical challenges based on real case studies and theoretical literature. In addition to AI, the module will explore the legal and regulatory issues associated with the development and use of autonomy, privacy-preserving technologies, blockchain, and quantum computing. Autonomy is defined as the ability of a system to act independently from a human operator.The module will focus on the application of autonomy in various systems, especially in the context of autonomous weapon systems. Further, privacy preserving technologies are newer technologies such as confidential computing, federated learning, synthetic data, or homomorphic encryption that allow to compute on data while preserving fundamental principles of privacy.This module will explore the application of selected privacy-enhancing technologies in various applications, e.g. the use of federated learning in healthcare to collect and commercialise medical data from hospitals or the use of confidential computing for sensitive data sharing across various organisations. Blockchain is a special type of privacy preserving technology based on a decentralized, distributed, and often public, digital ledger which facilitates the process of recording transactions and tracking assets.The module will explore various governance models of blockchain and their legal implications. Finally, quantum technology is a class of technology that works by using the principles of quantum mechanics to gain a functionality or performance which is otherwise unattainable.The module will discuss the role of law and regulation in the current and future development and application of quantum technologies.
View full module detailsSemester 1 & 2
Core
The project consists of a substantial written report and accompanying video presentation and software submission, completed by the student towards the end of their programme of studies. These are based on a major piece of work that involves applying material encountered in the taught component of the degree, and extending that knowledge with the student's contribution, under the guidance of a supervisor. The project lasts over both semesters, and usually involves software development, experimental or theoretical research, or a substantial analysis on a specific topic. Students are also expected to consider the legal, social, ethical and professional aspects of the project.
View full module detailsOptional modules for Year 3 (with PTY) - FHEQ Level 6
Students must select 4 optional modules out of a choice of 8 optional modules
Professional Training Year (PTY)
Semester 1 & 2
Core
This module supports students’ development of personal and professional attitudes and abilities appropriate to a Professional Training placement. It supports and facilitates self-reflection and transfer of learning from their Professional Training placement experiences to their final year of study and their future employment. The PTY module is concerned with Personal and Professional Development towards holistic academic and non-academic learning, and is a process that involves self-reflection, documented via the creation of a personal record, planning and monitoring progress towards the achievement of personal objectives. Development and learning may occur before and during the placement, and this is reflected in the assessment model as a progressive process. However, the graded assessment takes place primarily towards the end of the placement. Additionally, the module aims to enable students to evidence and evaluate their placement experiences and transfer that learning to other situations through written and presentation skills.
View full module detailsThis module supports students' development of personal and professional attitudes and abilities appropriate to a Professional Training placement. It supports and facilitates self-reflection and transfer of learning from their Professional Training placement experiences to their final year of study and their future employment. The PTY module is concerned with Personal and Professional Development towards holistic academic and non-academic learning, and is a process that involves self-reflection, documented via the creation of a personal record, planning and monitoring progress towards the achievement of personal objectives. Development and learning may occur before and during the placement, and this is reflected in the assessment model as a progressive process. However, the graded assessment takes place primarily towards the end of the placement. Additionally, the module aims to enable students to evidence and evaluate their placement experiences and transfer that learning to other situations through written skills.
View full module detailsOptional modules for Professional Training Year (PTY) -
Students must choose COMP009 or COMP010 year-long modules if studying full-time with PTY. Please note PTY year can be offered after Level 5 or Level 6 if doing MEng.
Year 4 - MEng with placement
Semester 1
Compulsory
Module purpose: This module was conceived to answer the SARTOR 3 requirement that each MEng student participates in a multi-disciplinary design activity. It involves students from Aerospace, Civil, Chemical, Electronic, Mechanical and Medical Engineering working in groups which contain at least 3, and often 4, disciplines. The projects are conceived by Royal Academy of Engineering (RAE) Visiting Professors from Industry (who enjoy the active support of their sponsoring organisation). It aims to emulate an intensive Industrial Design Project.
View full module detailsOptional
This module will introduce and explore the underlying concepts and technologies of virtual/augmented reality (VR/AR) and the emerging idea of the Metaverse. The module will also investigate the current and future challenges of the technologies and consider the impact it will have on industry and wider society.
View full module detailsMedical robotics is a rapidly developing industry that is vital to healthcare systems seeking better outcomes at reduced overall cost. This module introduces students to the workings of robots and how this is applied in solving both surgical and broader healthcare challenges. Students learn through lectures, practical sessions, tutorials and seminars requiring engagement with scientific literature. Case studies are a critical part of the module. These are industrially or research-based and require students to think about clinical conditions, ethical considerations and a range of attitudes to healthcare.The unit of assessment requires students to develop an understanding of the general theory behind robotics and identify the particularities applying to medical robots. The unit of assessment will also address the wider issues associated with medical robotics and their application. Practical sessions enable students to work with each other to solve problems and demonstrate the theoretical components of the module. An overarching series of lectures delivers critical technical information and links students¿ learning with case-studies to illustrate mechanical and medical issues. Seminars complement lectures and are designed for students to critically analyse, discuss and focus on particular aspects of medical robotic research in the scientific literature.
View full module detailsModule purpose: Advances related to energy efficiency issues and cost reductions have resulted in the rapid growth and deployment of networked devices and sensing/actuation systems that connect the physical world with the cyber world. This evolving framework, now recognized as the Artificial Intelligence of Things (AIoT), integrates IoT technologies with artificial intelligence (AI) to enhance automation, intelligence, and decision-making. AIoT incorporates several cutting-edge technologies, including wireless sensor networks, pervasive systems, ambient intelligence, context awareness, distributed systems, and machine learning-driven analytics. Module Overview: The advanced AIoT module is designed to provide a comprehensive understanding of how machine communications , coupled with AI, contribute to creating smart artificial intelligence-driven environments, focusing on networking and communication systems. The module provides an overview of the key concepts and enabling technologies for AIoT. It encompasses a cross-layer approach, allowing students to explore the practical aspects of sensors, actuators, and mainly communication systems for AIoT across physical, media access, and network layers. This includes security considerations, satellite AIoT, positioning and tracking for industrial applications, AIoT Platforms (Hardware, Software), protocols and standards (e.g. 6LowPAN, ZigBee, CoAp), semantic technologies, and data and information processing mechanisms. Also, the module explores AI-driven methodologies such as ensemble learning, multi-armed bandits for sequential decision-making, and lightweight machine learning Mmodels for AIoT applications. These techniques enhance real-time data analysis, predictive maintenance, anomaly detection, and adaptive control while ensuring computational efficiency.
View full module detailsThis module offers an introduction to the use of AI in society, work, media and communication, government and policy. It puts people ¿ as opposed to technology -- in the centre of AI, and highlights core considerations in planning for AI applications as a response to issues and considerations in the society. This is done by exploring varied positions of users and stakeholders in relation to AI, examining the suitability of AI and associated tools and methods to the productivity/progress/propagation in society. In this module we discuss the opportunities, but also the challenges, risks, threats and ethical implications involved in the use of AI in society.
View full module detailsSemester 2
Compulsory
Module purpose: This course offers an introduction to image processing and computer vision for those interested in the science and technology of machine vision. It provides background and the theory for building artificial systems that manipulate videos and images and alter or analyse their information content. This is done by various computer algorithms that are discussed, implemented and demonstrated.
View full module detailsOptional
The need for computational power and data storage continues to drive demand for more highly capable systems. Highly data intensive applications demand fast access to terabytes, petabytes, even exabytes of storage; processor intensive applications demand access to various types of processors in various configurations. Such applications are increasingly being developed in both scientific and industrial contexts and need to be variously scalable and supportable for large numbers of geographically distributed users. This module will provide insights into how Cloud Computing attempts to meet the varying needs of such applications.
View full module detailsThe module provides an application-focused tour of machine learning for real-world healthcare research and application from understanding various healthcare components, ethical concerns to pre-processing and analysing healthcare data for classification, survival and risk analysis, and early prediction tasks. The module requires and builds on the knowledge of basic machine learning, linear algebra, and familiarity with Python programming. Labs are designed to support understanding of the theory and enable development of practical skills required for future employability.
View full module detailsRecently, Artificial Intelligence (AI) has been playing a key role in the research and development of scientific and technological breakthroughs in many disciplines to solve real world problems, providing new foundations and steppingstones to foster more advances and solutions. In this context, AI has a great potential to play a transformative role in helping to achieve the United Nations Sustainable Development Goals (UNSDG), by providing new insights, enabling more efficient use of resources, and supporting a better understanding of complex systems that underpin the dynamics of people's lives and the planet's environment. Therefore, the purpose of this module is to present the key concepts with practical applications related to the development of more sustainable AI techniques (e.g. model, data and energy efficiency, bias and unfairness identification and mitigation, trustworthy AI, physics-informed neural networks etc.), and AI solutions to support UNSDGs (e.g. clean air, clean energy, clean water, waste management, smart manufacturing etc.).
View full module detailsThe module introduces general information and network security principles, challenges and goals and then focuses on main security mechanisms and protocols for protecting network communication across different layers of the Internet protocol stack. This will include discussion on various attacks on the networks, penetration testing tools and possible countermeasures to ensure protection of authentication, confidentiality and end-to-end security of communications. In labs students will be able to practice experience with various network security protocols and tools.
View full module detailsThe main application of machine learning is out-of-sample prediction. Prediction accuracy is typically evaluated in terms of squared error, where the error is difference between the prediction and the actual realization. In certain situations, such as forecasts of inflation or output from the Bank of England, an accurate prediction is enough. However, there are situations, like policy evaluation, in which we care about causal effects. Suppose that the Secretary of Education introduces three additional hours of mathematics in primary school to increase student GSE scores. Here the objective is to isolate the effect of additional hours of math on GSE score. In general, for each pupil, we have a lot of individual characteristics, which we need to control for. Data reduction techniques, such as LASSO, regression tree, random forest, help to eliminate all irrelevant information so that we can isolate the effect of the policy. This module is structured in two parts. In the first part, we review econometric tools for policy evaluation, such as instrumental variables, panel data, difference-in-difference, synthetic control, regression discontinuity. In the second part, we look at the same techniques when many instruments are available or many additional control variables are available.
View full module detailsOptional modules for Year 4 (with PTY) - FHEQ Level 7
Students may undertake up to 5 optional modules out of a choice of 9 optional modules. Select 2 optional modules in semester 1; Only 2 options in total from (EEEMO86, COMM068, COMM034) can be selected.
Teaching and learning
- Lectures
- Practical sessions
- Group work
- Online learning
- Seminars
- Tutorials
- Independent study
AssessmentWe use a variety of methods to assess you, including:
- Coursework
- Projects
- Reports
- Examinations
- Lab tests
- Presentations.
General course information
Contact hours
Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.
Timetable
New students will receive their personalised timetable in Welcome Week. In later semesters, two weeks before the start of semester.
Scheduled teaching can take place on any day of the week (Monday – Friday), with part-time classes normally scheduled on one or two days. Wednesday afternoons tend to be for sports and cultural activities.
View our code of practice for the scheduling of teaching and assessment (PDF) for more information.
Location
This course is based at Stag Hill campus. Stag Hill is the University's main campus and where the majority of our courses are taught.
We use a variety of methods to assess you, including:
- Coursework
- Projects
- Reports
- Examinations
- Lab tests
- Presentations.
Contact hours
Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.
Timetable
New students will receive their personalised timetable in Welcome Week. In later semesters, two weeks before the start of semester.
Scheduled teaching can take place on any day of the week (Monday – Friday), with part-time classes normally scheduled on one or two days. Wednesday afternoons tend to be for sports and cultural activities.
View our code of practice for the scheduling of teaching and assessment (PDF) for more information.
Location
This course is based at Stag Hill campus. Stag Hill is the University's main campus and where the majority of our courses are taught.
We offer careers information, advice and guidance to all students whilst studying with us, which is extended to our alumni for three years after leaving the University.
Over the last decade, our employment figures have been among the best in the UK, with 95 per cent of our computer science and electronic engineering graduates going on to employment or further study within 15 months of graduating (Graduate Outcomes Survey 2025, HESA).
As a graduate from this course, you will have developed in-demand skills and knowledge, ready to launch a career in computer science, artificial intelligence, agentic AI, GenAI, LLMs , robotics and autonomous systems, and cybersecurity. Your degree will also provide a strong foundation for a career in AI ethics, policy, and law.
Recent graduate roles
Our recent Computer Science graduates have gone on to roles including:
- Forensic Data Analyst, PwC
- AI developer at RLB
- Data Engineering at Brevan Howard
- Junior AI Engineer at Fivium
- Data Engineer at Booksy
- Data Manager at Metropolitan Police
- Technology Associate, Morgan Stanley
- Technical Architecture Consultant, Accenture UK Ltd
- Co-founded an AI company called Neural River
- Analyst Programmer, Avco Systems Ltd
- Computer Programmer, Stanhope-Seta
- Software Developer, ID Business Solution
- Software Engineer, Xceptor
- Testing and Continuous Delivery Architecture, Vodafone.
Extensive teaching laboratories, plus networked Linux and Windows computer suites with 24-hour access, are available to all our students.


Max Carter
Graduate - Computer Science BSc (Hons)
Getting your foot in the door early is crucial. If securing work experience proves difficult, focus on developing interesting side projects—they can be just as impressive to potential employers!


Liliya Yankova
Student - Computer Science BSc (Hons)
"I fell in love with Surrey’s campus from images online, but nothing compares to seeing it first-hand. The moment I set foot here, felt the atmosphere and met some of my course mates, I knew I had made the right decision."
Learn more about the qualifications we typically accept to study this course at Surrey.
Typical offer
- BSc (Hons):
- ABB
- Required subjects: Mathematics
- MEng:
- AAA-AAB
- Required subjects: Mathematics
Please note: A-level General Studies and A-level Critical Thinking are not accepted.
GCSE or equivalent: English Language at Grade 4 (C).
- BSc (Hons):
- DDD. Additionally, A-level Mathematics at Grade B.
- MEng:
- D*DD-DDD. Additionally, A-level Mathematics at Grade B.
GCSE or equivalent: English Language at Grade 4 (C).
- BEng (Hons):
- 33
- Required subjects: Mathematics Analysis and Approaches HL5/SL6 or Mathematics Applications and Interpretations HL5.
- MEng:
- 35-34
- Required subjects: Mathematics Analysis and Approaches HL5/SL6 or Mathematics Applications and Interpretations HL5.
GCSE or equivalent: English A HL4/SL4 or English B HL5/SL6.
- BSc (Hons):
- 78%.
- Required subjects: At least grade 7.5 in Mathematics (5 Period).
- MEng:
- 85-82%.
- Required subjects: At least grade 7.5 in Mathematics (5 Period).
GCSE or equivalent: English Language (1/2) - 6 or English Language (3) - 7.
- BSc (Hons):
- QQAA-recognised Access to Higher Education Diploma, with 45 Level 3 credits including 30 Level 3 Credits at Distinction and 15 Level 3 Credits at Merit. Additionally, A-level Mathematics at Grade B.
- MEng:
- QAA-recognised Access to Higher Education Diploma, with 45 Level 3 credits including 45 Level 3 credits at Distinction - 39 Level 3 Credits at Distinction and 6 Level 3 Credits at Merit. Additionally, A-level Mathematics at Grade B.
GCSE or equivalent: English Language at Grade 4 (C).
- BSc (Hons):
- 78%.
- Required subjects: At least grade 7.5 in Mathematics (5 Period).
- MEng:
- 85-82%.
- Required subjects: At least grade 7.5 in Mathematics (5 Period).
GCSE or equivalent: English Language (1/2) - 6 or English Language (3) - 7.
- BSc (Hons):
- AABBB.
- Required subjects: Mathematics.
- MEng:
- AAAAB-AAABB.
- Required subjects: Mathematics.
GCSE or equivalent: English Language Scottish National 5 - grade C.
- BSc (Hons):
- ABB from a combination of the Advanced Skills Baccalaureate Wales and two A-levels
- Required subjects: A-level Mathematics.
- MEng:
- AAA-AAB from a combination of the Advanced Skills Baccalaureate Wales and two A-levels
- Required subjects: A-level Mathematics.
Please note: A-level General Studies and A-level Critical Thinking are not accepted.
GCSE or equivalent: Please check the A-level dropdown for the required GCSE levels.
This route is only applicable to the MEng course.
Applicants taking the Extended Project Qualification (EPQ) will receive our standard A-level offer, plus an alternate offer of one A-level grade lower, subject to achieving an A grade in the EPQ. The one grade reduction will not apply to any required subjects.
This grade reduction will not combine with other grade reduction policies, such as contextual admissions policy or In2Surrey.
English language requirements
IELTS Academic: 6.0 overall with 5.5 in each element.
View the other English language qualifications that we accept.
If you do not currently meet the level required for your programme, we offer intensive pre-sessional English language courses, designed to take you to the level of English ability and skill required for your studies here.


International Foundation Year
If you are an international student and you don’t meet the entry requirements for this degree, we offer the International Foundation Year at the Surrey International Study Centre. Upon successful completion, you can progress to this degree course.
Selection process
We normally make offers in terms of grades.
If you are a suitable candidate you will be invited to an offer holder event. During your visit to the University you can find out more about the course and meet staff and students.
Recognition of prior learning
We recognise that many students enter their higher education course with valuable knowledge and skills developed through a range of professional, vocational and community contexts.
If this applies to you, the recognition of prior learning (RPL) process may allow you to join a course without the formal entry requirements or enter your course at a point appropriate to your previous learning and experience.
There are restrictions on RPL for some courses and fees may be payable for certain claims. Please see the code of practice for recognition of prior learning and prior credit: taught programmes (PDF) for further information.
Contextual offers
Did you know eligible students receive support through their application to Surrey, which could include a grade reduction on offer?
Fees
Explore UKCISA’s website for more information if you are unsure whether you are a UK or overseas student. View the list of fees for all undergraduate courses.
Payment schedule
- Students with Tuition Fee Loan: the Student Loans Company pay fees in line with their schedule.
- Students without a Tuition Fee Loan: pay their fees either in full at the beginning of the programme or in two instalments as follows:
- 50% payable 10 days after the invoice date (expected to be early October of each academic year)
- 50% in January of the same academic year.
The exact date(s) will be on invoices. Students on part-time programmes where fees are paid on a modular basis, cannot pay fees by instalment.
- Sponsored students: must provide us with valid sponsorship information that covers the period of study.
Professional training placement fees
Professional Training placement year fees are approximately 20% of the full-time fee for the academic year in which you undertake your placement.
Our award-winning Professional Training placement scheme gives you the chance to spend a year in industry, either in the UK or abroad.
We have thousands of placement providers to choose from, most of which offer pay. So, become one of our many students who have had their lives and career choices transformed.
Statistics
Placement Statistics
95%
of students who did a placement entered into graduate level employment*
80%
of placements are paid, with 57% paying between £18,000 - £30,000
48%
of our students have been offered a graduate role from their placement provider**
*HESA 2024
**Professional Training Year Returners Survey 2023
Applying for placements
Students are generally not placed by the University. But we offer support and guidance throughout the process, with access to a vacancy site of placement opportunities.
Find out more about the application process.


Discover, develop and dive in
Find out how students at Surrey developed their skills in industry by undertaking a placement year.
Discover, develop and dive in
Find out how students at Surrey developed their skills in industry by undertaking a placement year.
Study and work abroad
Studying at Surrey opens a world of opportunity. Take advantage of our study and work abroad partnerships, explore the world, and expand your skills for the graduate job market.
The opportunities abroad vary depending on the course, but options include study exchanges, work/research placements, summer programmes, and recent graduate internships. Financial support is available through various grants and bursaries, as well as Student Finance.
Perhaps you would like to volunteer in India or learn about Brazilian business and culture in São Paulo during your summer holidays? With 140+ opportunities in 36+ different countries worldwide, there is something for everyone. Explore your options via our search tool and find out more about our current partner universities and organisations.
Apply for your chosen course online through UCAS, with the following course and institution codes.
About the University of Surrey
Need more information?
Contact our Admissions team or talk to a current University of Surrey student online.
Terms and conditions
When you accept an offer to study at the University of Surrey, you are agreeing to follow our policies and procedures, student regulations, and terms and conditions.
We provide these terms and conditions at offer stage and are shown again at registration. You will be asked to accept these terms and conditions when you accept the offer made to you.
View our generic registration terms and conditions (PDF) for the 2025/26 academic year, as a guide on what to expect.
Disclaimer
This online prospectus has been published in advance of the academic year to which it applies.
Whilst we have done everything possible to ensure this information is accurate, some changes may happen between publishing and the start of the course.
It is important to check this website for any updates before you apply for a course with us. Read our full disclaimer.