You will execute a cyber security project from conception to completion, working to meet a client brief and applying the concepts and skills gained so far in a practical setting.

Working in a team, you will develop your skills in prototyping, project planning, management, design, user evaluation and testing strategies. Your group will be expected to deliver reports, code, and demonstrate a working system by the project’s conclusion.

Projects will either seek to build a system that may be used as a cyber security tool, for example a vulnerability scanner, or follow secure software design methodologies to build an application, such as a communication tool. Lectures will advise you on how to approach teamwork, project management, risks, and costings so that you have a sound base for managing collaborative projects, as well as continue to develop your cyber security awareness and techniques.

Human-computer interaction (HCI) is concerned with all aspects of designing, building, evaluating, and studying systems that involve human interaction.

From a computing perspective, the focus is on enabling interaction through user interfaces and on creating interactive systems that provide a positive user experience. The module introduces you to the foundations of HCI, where you delve into human behaviour, technologies for interaction and human-centred design. You will review human perception, cognition and action, and relate these to design principles and guidelines. As part of this, you will discuss different examples of user interfaces and key technologies such as pointing. You will then be introduced to the practical methods for designing and evaluating, including legal, social, ethical and professional considerations in relation to people and society, such as inclusive design practices, bias, and privacy.

Investigate the deeper concepts that underpin computer networking and operating systems. You will explore the role, operation, and design rationale of the IP protocol suite that enables the global internet. Taking a top-down approach, discover how protocols such as HTTP, DNS, and TCP/IP operate on a fundamental level, and the metrics and tools we use to evaluate the performance of computer networks.

Core operating system concepts will be built upon and expanded to develop an in-depth understanding of the components of an operating system such as the kernel, scheduling, access control, memory management and file systems. Using simulators, you will explore first-hand how data is efficiently and safely routed across the global internet. You will study the interface between networks and operating systems, and how the concept of virtualisation has transformed the way systems and networks make efficient use of hardware resources.

An introduction to two essential concepts in modern computing systems, cyber security and data engineering. We explore the building blocks of the Authentication, Authorisation and Accountability (AAA) framework, including access control models, security policies and mechanisms. You will review the main categories of existing cryptosystems to understand their security properties, discuss basic concepts of systems security, study the common approaches and tools that attackers use and gain first-hand experience tackling the weaknesses that can be present in real-world systems through guided work in a highly controlled, small-group practical lab.

You will gain a practical and theoretical background in the design, implementation and use of database management systems. This will incorporate the consideration of information quality and security, Entity-Relationship Models, the relational model and the data normalisation process, and alternative schema definitions, SQL, NoSQL and Object-Oriented data models, big data, as well as transaction processing and concurrency control.

Delve into the key principles of artificial intelligence (AI), touching on the core concepts and philosophy of AI and discussing its presence and ethical challenges in the modern world. Throughout, you will unearth the underlying principles of search spaces, knowledge representation and inference logic that form the core of rule-based systems, before learning the principles of machine learning, clustering, classification, linear regression and neural networks.

From this, you will have the grounding necessary to progress to modules in topics such as machine learning, computer vision, and NLP. You will also gain a deeper understanding of computational problem solving, exploring the very nature of computability, including non-deterministic polynomial (NP) complexity classes such as NP-hard, NP-complete and problems which cannot be solved. Be introduced to classical algorithmic approaches to problem solving including divide and conquer, recursion, and parallel approaches, exploring their relative merits for different classes of problem.

Computer architecture has now reached a critical juncture where we are witnessing a steep change in computer performance, not due to the increased performance of individual processors, but through the inclusion of many, sometimes even thousands, of processor cores in a single computer. This requires new ways of thinking about these concurrent systems, and operating systems in general. Dive into the theory and practical application of advanced operating systems (OS) and associated hardware concepts. Through a combination of lab exercises and lectures, you will investigate the ways that modern operating systems are optimised to extract the maximum performance and efficiency from 21st century computer hardware. As part of this, you will use contemporary software tools and techniques to create high performance applications that exploit multi-threaded instruction parallelism whilst avoiding race conditions, deadlock and livelock, and utilise GPUs to exploit data parallelism.

Extended reality (XR) refers to the interactive technologies that blend virtual and physical worlds into a hybrid environment or immersive experience. The technology is based on multi-modal platforms that integrate the use of wearable computing. In this module, you will explore different uses of extended reality within the Reality-Virtuality Continuum and identify the needs and means of augmenting human senses.

You will take an applied approach to the design, implementation, deployment, and evaluation of systems that are used to create an XR environment and deliver an immersive experience. To do this, you will study the latest trends in research, emerging technologies, and novel tools, with an analytical focus that assesses the socio-ethical impacts that may result from widespread usage of XR. A key topic will be the computer graphics technology that enables extended realities to exist visually, exploring the fundamental concepts related to visual content generation through relevant theory and practice using current game engines.

The internet and the world wide web have now invaded every aspect of our lives, from ecommerce and entertainment to logistics and social media. Increasingly, application software is no longer written for specific devices, but for internet web browsers. The internet has replaced operating systems as the de-facto platform for application development, making an already global phenomenon truly impactful.

This module explores the various approaches to the development of internet applications, investigating both the client and server-sides, and discussing the trade-off of performance, scalability, privacy and trust associated with these approaches. You will review the role of ‘cloud infrastructures’ (federated distributed computation) in the provision and management of internet applications. Through interactive lectures and practical sessions, you will study common frameworks for client-side application development and create and deploy an internet application from first principles.

Distributed systems are the foundation upon which modern large-scale infrastructures are built, such as Cloud and service-oriented architectures (also known as ‘as a service’). You’ll investigate the cryptographic techniques used to build such systems, and secure distributed systems themselves.

You’ll study the design approaches to constructing a secure distributed system, including the common vulnerabilities and attack surfaces associated with distributed systems, and the widely adopted design patterns used to mitigate them. To ensure the correctness of such systems, you will be introduced to formal verification techniques covering system specification and the verification of their correctness. This is imperative for systems that form the foundation of modern infrastructures or when we require security guarantees in mission-critical scenarios. Formal languages are used to define precise system specifications, and automated verification techniques verify their correctness. The languages enable the modelling of distributed systems and algorithms, and the verification of properties to prove their correctness.

Artificial Intelligence (AI) is being rapidly adopted in both research and industry, via technologies such as generative AI and large language models (LLM). They are being used for a range of applications by enhancing cyber security through the detection of anomalies, identifying threats, and monitoring abnormal activities. However, AI itself is susceptible to various attacks, such as prompt injection, data leakages, jailbreaking, bypassing guardrails, model backdoors, and more.

In this module, you will learn the fundamentals of AI for security and security for AI. This encompasses both how AI can be leveraged to augment and improve established cyber security techniques (from firewalls, risk analysis, to attack detection), as well as the emerging attacks against AI itself (data poisoning, extraction, membership inference). You’ll learn how AI is being used to revolutionise the established cyber security field, the emerging threats of adversarial attacks against ML models and data, and how to mitigate those attack.

Understand security threats to cyber physical systems (CPS), such as industrial control systems, Internet of Things and connected vehicles, as well as techniques to mitigate these threats. Compared to traditional computer systems, CPS have limited resources and are typically deployed into a physical environment. This impacts the implementation of security techniques, as due to the environment they are deployed in you must consider both digital and physical attacks.

This module introduces how to identify the appropriate security techniques to use for a CPS. You will come to understand how to write secure applications for CPS and which alternative mitigations are appropriate. You will also learn how the limitations of these systems impact the guarantee of security. In addition to this, you will examine the safety and privacy threats facing CPS and explore the interconnectivity between them and security.

You will undertake a substantial individual project on a cyber security topic, typically involving the principled design, implementation, and evaluation of a substantial piece of software, experimental study, or theoretical work. To assist in this, a cyber security academic will provide a large range of project ideas covering the breadth of our School’s expertise, which you will rank by level of interest before being allocated to a supervisor. You will also have the opportunity to write your own project idea and find a supervisor that would like to support you, and projects can be carried out in collaboration with an external partner, such as a company.

Throughout the project, you will be expected to attend regular one-to-one meetings with your supervisor, who will provide guidance and feedback as you explore your topic and complete previously agreed goals.

Computer networks have experienced an exponential growth in traffic and size since the early days of the internet. Packet network technologies underpin every aspect of our daily life. On this module, you will investigate how network technologies have evolved to cope with increasing demands, the architecture of devices, and protocols that facilitate end-to-end connectivity, while allowing control of connectivity properties like bandwidth and latency. You will explore cutting-edge research and industry perspectives regarding the challenges that face production network technologies, such as performance and security, and speculate on the future direction networking will take.

Practical sessions introduce network emulation and simulation technologies, where you will recreate realistic network testbeds. You will gain experience using open-source software frameworks to implement, configure and test common network functionalities, such as routing and firewalling.

Dive into alternative programming language paradigms, beyond imperative and object-oriented programming. Emphasis is placed on functional programming languages and their unique constraints and features, such as more expressive type systems, immutability, pure functions and side-effects, lambdas, higher order functions, currying, map/reduce and pattern matching. You will also explore why functional languages bring about increased reliability and scalability and how they are now experiencing a resurgence within the software industry. Through hands-on laboratory sessions, you will learn a functional programming language, such as Haskell, and see how functional programming concepts are being integrated in mainstream programming languages, such as Java, Python and JavaScript, to create versatile multi-paradigm programming environments.

Learn how to teach computer science as a discipline, including organising engaging activities that address the digital skills gap, and inspiring new computer scientists. Through practical sessions, you will build a foundational understanding of computing pedagogy, learning to recognise how learners study computer science and arrange teaching to respond to their needs. You’ll explore the instruments and methods for effective teaching practices, considering UK and global contexts, and the differences within primary, secondary, and higher education.

The importance of equality, diversity, and inclusion (EDI), ethics, safeguarding and integrity considerations in education will be highlighted throughout. You will also learn how to plan or conduct teaching or outreach activities in schools and support the development of digital capabilities of young people in Lancashire.

Computer vision is a branch of artificial intelligence which aims to build computer-based systems that can interpret and draw meaning from digital images. This module digs into the fundamentals of image formation, information relating to the human visual system, and image interpretation methodologies including convolution, edge detection and feature extraction, and comparison. You will tackle key problems in current research, including semantic segmentation, object detection and three-dimensional image interpretation. You will cover a range of approaches, from low-level image processing to convolutional neural networks. At the end of the module, you will be equipped to construct software components that implement contemporary image processing and computer vision algorithms and recognise issues within computer vision in order to develop and evaluate solutions.

Digital Health explores the utilisation of digital technologies in healthcare. These technologies have an ever-growing role to play in improving health systems and public health, as well as increasing and improving access to health services. Discover the practical applications, implications, and how to enable technologies of digital health. You will survey sensor technologies that permit remote and automated patient monitoring and study the technologies and processes that enable patient-driven healthcare. You will also investigate the structure of health data in electronic health records and methods for the evaluation of digital health solutions. Alongside these applied topics, you’ll also learn about data governance and the ethical issues surrounding digital health technologies, policy, and regulation.

Large scale distributed computing systems are now commonplace, implemented using ‘cloud infrastructures’ where computing and storage resources are pooled into data centres around the globe. In scientific terms, these are examples of distributed systems. Learn about the fundamental principles that underpin modern distributed systems, the abstractions on which they are based, and their characteristics. Emphasis is placed on the scalability and fault-tolerance of these systems, and you will dive into the commonly used frameworks for distributed systems, such as Google’s infrastructure, and highly distributed peer to peer approaches. Small group practical labs reinforce theory through hands-on experience of distributed systems development.

Understand the challenges associated with developing firmware for embedded systems, which is increasingly common in everyday appliances following a rise in cyber-physical systems, smart cities, and the Internet of Things. You will engage with relevant hardware and low-level programming as you study the architecture of microcontrollers (highly specialised, resource constrained computer processors that power embedded systems).

Building on this, you will then learn about the state-of-the-art software development processes that facilitate the writing of highly efficient code for such devices. You’ll become familiar with industry standard protocols and techniques for integrating peripherals with microcontrollers, and the low power wireless network communication technologies that enable their interconnection. The module will provide you with opportunities to work with a variety of embedded systems in practical sessions.

All programming languages are based on theoretical principles of formal language theory. In this module, you dive deep into formal languages representation and grammars, and how they relate to programming language compilers and interpreters. You will study formal language syntax and semantics, phrase structure grammars, and the Chomsky hierarchy. You will learn how to classify languages and explore the concepts of ambiguity in context-free grammar and its implications. In particular, you will learn about the compilation process including lexical analysis and syntactic analysis, recursive descent parsers and semantic analysis. Finally, you get to investigate the synthesis phase, where intermediate representations, target languages and structures lead to code generation.

Delve into machine learning, a fundamental concept in artificial intelligence that enables a computer to learn how to perform a task from data rather than traditional programming. In this module, you will study the key ideas and techniques behind machine learning and develop the practical skills needed to understand the implications and potential of machine learning in business and society. You will begin by looking at real-world problems, challenges, and fundamental techniques in current methodology. Building on this, you will cover a variety of approaches to machine learning, from decision trees to a wide range of deep neural networks, including multilayer perceptrons, convolutional neural networks, long short-term memory, autoencoder and generative adversarial networks.

Gain a broad understanding of Natural Language Processing (NLP), a branch of artificial intelligence where computational methods are used to analyse and understand human languages. Throughout the module, you will be exposed to the core concepts surrounding the NLP pipeline, covering methods and techniques for data collection, cleaning, tokenisation, and annotation using a hierarchy of linguistic levels (e.g. morphology, syntax, and semantics). You will experiment with and comparatively evaluate different methods and techniques, including rule-based, probabilistic, machine learning and deep learning approaches. You will also learn to apply and adapt NLP pipelines and tools to real-world text mining scenarios and problems, including examples such as health and finance. Key issues such as ethical data collection, bias in language models, and employing sustainable computing methods will also be touched upon throughout.

We introduce you to quantum computing's core principles and applications, contrasting its capabilities with classical systems. You will master Dirac notation and essential linear algebra, before examining quantum mechanics' four postulates, including qubits, gates, and circuit models. You will cover fundamental algorithms, including Deutsch's algorithm (implemented via Qiskit), Simon's problem, Bernstein-Vazirani, Grover's search (with BBBV Theorem analysis), and Shor's factorisation algorithm's impact on RSA cryptography.

Quantum cryptography components address post-quantum security and QKD protocols, while quantum information theory explores superdense coding, the no-cloning theorem and teleportation. The module concludes with emerging concepts like quantum money and the Elitzur-Vaidman bomb tester. Combining theoretical foundations with practical programming exercises, you will develop a critical understanding of both quantum computing's potential and current technological limitations, preparing you for advanced study or research in this rapidly evolving field.

Computing plays a pivotal role in addressing growing energy costs, greenhouse emissions, and the climate crisis. Whilst we can use computing and its associated digital technologies to shape a greener society (as well as create more energy-efficient software and hardware), there exist important trade-offs in respect to economic cost, engineering effort, and environmental impact. Explore key concepts associated with creating sustainable computing, spanning from how a processor uses electricity to how computers shape a greener economy and society. You will study the methods to create more energy-efficient code, energy-aware device mechanisms, as well as the benefits and drawbacks of computing and digital technology with respect to its impacts upon the environment and economy.

In your final year, you will undertake a substantial project that focuses on a particular specification, design, implementation and/or evaluation. Through this, you will tackle a real-world problem that aims to develop your existing knowledge, understanding and skills within your chosen discipline. The project is typically achieved in conjunction with your placement; however, it can be completed at the University.

Suggested topics will be provided by industry and vetted by our academics to ensure they offer the appropriate depth. If no suitable project with industry can be found, one will be provided by academic staff. You will have access to weekly meetings with an academic who will provide guidance and ensure the necessary level of academic rigour is maintained.

In the second semester of your final year, you will complete a 10-week placement. The University works with a range of organisations, from SMEs to large corporations and third-sector organisations, which you can be placed in.

During your placement, you will gain first-hand experience of working in a contemporary ICT-related environment, developing an understanding of professional practices and codes of conduct in industrial, commercial and professional settings. The organisation will set tasks that call upon the knowledge and experience gained throughout your degree, allowing you to apply it in a professional setting. Through an initial matching and application process, we ensure the biggest possible overlap between your interest and company requirements.

You will be assigned an academic supervisor who will guide and assist you during your placement. Placements will be assigned during the first semester.

Computer scientists often face problems for which there are no ready answers, therefore requiring future research. In this module, you will deepen your understanding of research methodology, the ‘classic’ empirical survey methods, case study, ethnography and experiment, and design and innovation as the context in which computer scientists apply research methods.

On a fundamental level, you will explore how empirical research involves sampling, data collection, study design and data analysis, and how each of these involves trade-offs that can limit the validity of results gained and conclusions drawn. On a practical level, you will engage in a collaborative innovation project through which you can practice the application of methods in design and evaluation of novel interactive solutions.

Computer networks have experienced an exponential growth in traffic and size since the early days of the internet. Packet network technologies underpin every aspect of our daily life. On this module, you will investigate how network technologies have evolved to cope with increasing demands, the architecture of devices, and protocols that facilitate end-to-end connectivity, while allowing control of connectivity properties like bandwidth and latency. You will explore cutting-edge research and industry perspectives regarding the challenges that face production network technologies, such as performance and security, and speculate on the future direction networking will take.

Practical sessions introduce network emulation and simulation technologies, where you will recreate realistic network testbeds. You will gain experience using open-source software frameworks to implement, configure and test common network functionalities, such as routing and firewalling.

Dive into alternative programming language paradigms, beyond imperative and object-oriented programming. Emphasis is placed on functional programming languages and their unique constraints and features, such as more expressive type systems, immutability, pure functions and side-effects, lambdas, higher order functions, currying, map/reduce, and pattern matching. You will also explore why functional languages bring about increased reliability and scalability and how they are now experiencing a resurgence within the software industry.

Through hands-on laboratory sessions, you will learn a functional programming language, such as Haskell, and see how functional programming concepts are being integrated in mainstream programming languages, such as Java, Python and JavaScript, to create versatile multi-paradigm programming environments.

Digital Health explores the utilisation of digital technologies in healthcare. These technologies have an ever-growing role to play in improving health systems and public health, as well as increasing and improving access to health services. Discover the practical applications, implications, and how to enable technologies of digital health. You will survey sensor technologies that permit remote and automated patient monitoring and study the technologies and processes that enable patient-driven healthcare. You will also investigate the structure of health data in electronic health records and methods for the evaluation of digital health solutions. Alongside these applied topics, you’ll also learn about data governance and the ethical issues surrounding digital health technologies, policy, and regulation.

Large scale distributed computing systems are now commonplace, implemented using ‘cloud infrastructures’ where computing and storage resources are pooled into data centres around the globe. In scientific terms, these are examples of distributed systems. Learn about the fundamental principles that underpin modern distributed systems, the abstractions on which they are based, and their characteristics. Emphasis is placed on the scalability and fault-tolerance of these systems, and you will dive into the commonly used frameworks for distributed systems, such as Google’s infrastructure, and highly distributed peer to peer approaches. Small group practical labs reinforce theory through hands-on experience of distributed systems development.

All programming languages are based on theoretical principles of formal language theory. In this module, you dive deep into formal languages representation and grammars, and how they relate to programming language compilers and interpreters. You will study formal language syntax and semantics, phrase structure grammars, and the Chomsky hierarchy. You will learn how to classify languages and explore the concepts of ambiguity in context-free grammar and its implications. In particular, you will learn about the compilation process including lexical analysis and syntactic analysis, recursive descent parsers and semantic analysis. Finally, you get to investigate the synthesis phase, where intermediate representations, target languages and structures lead to code generation.

Delve into machine learning, a fundamental concept in artificial intelligence that enables a computer to learn how to perform a task from data rather than traditional programming. In this module, you will study the key ideas and techniques behind machine learning and develop the practical skills needed to understand the implications and potential of machine learning in business and society. You will begin by looking at real-world problems, challenges, and fundamental techniques in current methodology. Building on this, you will cover a variety of approaches to machine learning, from decision trees to a wide range of deep neural networks, including multilayer perceptrons, convolutional neural networks, long short-term memory, autoencoder and generative adversarial networks.