Autumn 2026

This module provides you with a thorough yet approachable foundation in applied machine learning, carefully balancing essential theory with practical experience across a variety of real world domains. Starting with the core principles that explain how machines learn from data, you gradually develop competence in supervised and unsupervised learning, as well as in emerging approaches that are shaping the future of the field.
You gain the understanding required to choose suitable methods and technical skills needed to implement, analyse and critically evaluate results using industry-standard tools such as PyTorch.
A key emphasis of the module is applying machine learning to real-world problems, rather than studying algorithms in isolation. You will explore each technique through realistic challenges drawn from sectors such as healthcare, finance, environmental monitoring, and wider society.
This module covers the fundamentals of machine learning lifecycle, from preparing and analysing data, to selecting and training models, evaluating performance, and considering deployment. Ethical and societal responsibilities, particularly those associated with automated decision making, are embedded throughout the module. You will also study the significance of generative and agentic AI systems and their implications for applied work.

This module provides a core foundation for students entering data science from a wide range of academic and professional background. The module is designed to build confidence and capability in working with data, introducing the key concepts, methods and tools that underpin modern analytical practice.
You will develop fluency in the full data analytics workflow, from sourcing, cleaning, and transforming raw data, through exploratory analysis and statistical reasoning, to producing meaningful insights that support decision-making. The module emphasises the critical thinking required to ask effective analytical questions and interpret results responsibly, with a clear understanding of ethical and professional considerations.
You will learn how visual representation helps reveal patterns, highlight anomalies and communicate findings in compelling and accessible ways. Through hands-on lab activities and applied tasks, you will develop the ability to create clear, accurate and purposeful visualisations tailored to different audiences.

By engaging with industry-standard tools, including widely used Python libraries and contemporary data technologies, you will build the practical skills required in professional data roles across diverse sectors. By the end of the module, you will acquire the skills to work independently with datasets and present analytical outputs clearly, persuasively, and ethically.

This module covers how construction organisation carries out estimating and costing, tendering and financial accounting and control along with human resource management practices. You will be introduced to standard measures of measurement and the New Rules of Measurement, order of cost estimates and the wider estimating process in order to cost construction projects. Topics on tendering practices will concentrate on the construction manager’s responsibilities at tender stage. A full review and analysis of a live project brief tender documentation pack will develop your skills required to produce a professional tender submission; focusing on the design proposals, method statements, tender programme, logistics planning and risk management to produce a comprehensive technical submission. You will develop understanding of how construction organisations manage their finances and human resources. The financial management covers management of finances in the project and accounting concepts and conventions, objectives of financial statements and their uses. You will develop an understanding of HRM functions carried out by the Construction Managers in developing and maintaining professional relationships with colleagues and partner organisations and explore productivity improvement techniques are explored. This module adopts a practice-based and experiential learning approach to ensure students engage in real-world construction management scenarios. The learning experience is designed to be research-informed and industry-driven, incorporating guest lectures from professionals, hands-on workshops using industry software, problem-based learning (PBL) activities, and collaborative projects. Lectures provide theoretical foundations, while seminars and tutorials focus on case studies, role-playing exercises, and critical discussions. The use of construction project simulations and live industry projects ensures that students develop both the technical and managerial skills needed for professional practice.

This studio module develops architectural design as an experimental and iterative process, with environmental thinking at its core. Building on Level 4 foundations, you will design a small to medium-scale project shaped by context, climate, light, orientation and ventilation. Through drawing, model-making and diagramming, you will test how environmental conditions influence form, space and experience. Emphasis is placed on exploration and design development rather than technical calculation, encouraging critical reflection and creative risk-taking. Studio tutorials, peer discussion and critique support the communication and refinement of your ideas, preparing you for more complex and integrated design challenges.

This module will provide you with a comprehensive understanding of fluid mechanics, focusing on the principles that govern fluid behaviour and their applications in civil engineering. You will develop knowledge of fluid statics and dynamics, including the equations that describe fluid flow and their use in designing pipes, open channels, and hydraulic machines. You will explore fluid mechanics principles in real-world engineering contexts, learning how to analyse fluid behaviour and apply theoretical concepts to practical scenarios. The module also focuses on designing systems for fluid transport, emphasizing problem-solving, critical thinking, and technical skills essential for professional engineering roles. Through laboratory work, computational modelling, and site visits, you will apply your knowledge to practical case studies. Assessment is through in-class tests and laboratory reports, enabling you to demonstrate both conceptual understanding and practical problem-solving ability. This module will equip you with transferable skills in mathematical analysis, problem-solving, and technical reporting, which are essential for future employment in civil engineering and related industries. Note: To pass this module, Civil Engineering students must achieve a weighted average of 40% or above across all pieces of summative assessment, and a mark of 30% or above in each separate assessment.

This module introduces you to the essential mathematical concepts that underpin modern data science, presented in an accessible, application-focused way for students from non-STEM backgrounds. Rather than emphasizing abstract theory, the module focuses on how mathematical ideas are used in real-world data analysis and decision-making.

You will explore key topics such as statistics and probability for interpreting data, basic calculus for understanding change and optimisation, and linear algebra concepts (including vectors and matrices) that support common data science techniques. These topics are taught through practical examples and case studies, enabling students to apply mathematical thinking directly to business, social, and organisational problems.

The module aims to build confidence in using mathematics as a practical tool for data-driven problem solving. By the end of the module, you will be able to formulate data-related problems, apply appropriate mathematical methods, interpret analytical results, and critically evaluate outputs from data science and machine learning models in real-world contexts.

This module develops the knowledge and skills required to analyse and design structural elements using engineering principles and Eurocodes. It covers the analysis of statically indeterminate structures through flexibility, stiffness and matrix methods. You will develop the ability to determine design actions, load combinations and structural stability, forming the basis for safe and efficient structural design. Building on structural analysis, the module introduces the design of reinforced concrete, steel, timber and masonry structural elements in accordance with relevant Eurocodes. You will also gain experience in using commercial structural analysis and design software to model structures, interpret results and critically evaluate software outputs alongside manual calculations. Practical application is emphasized through hands-on exercises and projects. The module links to Interdisciplinary Design Project 2, enabling you to apply theoretical and analytical skills in a real-world context. It includes lectures, problem classes, and guest lectures from industry experts. You will learn through lectures, tutorials and practical applications. You will be assessed through in-class tests and an individual design report. The skills developed in this module align with industry expectations, preparing students for careers in structural design, consulting, and construction management. Note: To pass this module, Civil Engineering students must achieve a weighted average of 40% or above across all pieces of summative assessment, and a mark of 30% or above in each separate assessment.

Mathematics and Statistics for Data Science teaches the underpinning mathematical and statistical aspects of data science in terms that are not only relevant to the successful and optimised implementation of solutions to problems in the field but also can be used as sole analytical tools. You will be exposed to the topics of statistics, probabilities, calculus, linear algebra, vector and matrix operations as well as mathematical operations on series that are important for understanding and developing solutions.

The module builds upon the knowledge and understanding developed from the level 4 Construction Science, Technology and Materials 1 with a focus on the technology of framed construction and new methods of construction. You will develop a deeper understanding of contemporary construction technology principles in framed buildings including basements. It addresses the superstructure to include types of frames, different envelope systems and building services suitable for such building types.The flexibility of the internal space and finishes is explained with the associated technology, including fire and life safety. Safe working practices are considered in the introduction to each element of construction technology as emphasised by the relevant regulations. Sustainability considerations will be integrated throughout the module, particularly in respect of energy-efficient design. By engaging with this module, you will develop analytical and problem-solving skills applicable to careers in architectural technology, construction management, surveying and sustainable engineering.

This module introduces you to the fundamental principles of construction technology and materials, focusing on their application in low-rise domestic buildings. It covers the mechanical and physical properties of materials, material selection for sustainability, and construction technology from foundations, walls, roofs and floors, together with building services. You will participate in practical laboratory sessions and technical workshops to investigate the properties and performance of construction materials and building systems. These practical activities reinforce lecture content and develop your understanding of construction technology, material behaviour and environmental building performance. You will also learn the fundamental concepts of environmental science as it applies to low rise buildings, particularly in terms of heat transfer and ventilations, and how this influences the selection of building materials to comply with sustainability targets and regulations. Key to this is the heating and cooling of buildings and you will learn about heat pump technology, renewable energy sources and designing for grid decarbonisation. On successful completion, you will be able to evaluate material properties, analyse building performance, select appropriate construction technology, and apply environmental and safety principles in construction. This module will enhance your ability to analyse construction materials and technology choices, skills that are essential for careers in architectural technology, construction management, and surveying. You will develop technical report-writing skills, problem-solving abilities, and practical knowledge of sustainability standards, all of which are highly valued in the industry. Level 4 modules are designed wherever possible to have a focus on preparing you for university life through various initiatives that foster growth. This module is designed to support you in your transition into Higher Education while developing essential skills to enhance success. There are a number of additional support initiatives which you can engage with, which include induction sessions, academic guidance tutors (AGT), student support coaches, mentoring programmes and various areas of digital support.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to complete at postgraduate level. This module provides an opportunity for students to undertake a focused independent project on an approved subject-related topic, balancing directed and independent learning at an advanced level. The topic will relate directly to the student’s home programme by allowing the student to pursue an aspect of intellectual or professional interest that connects to their specialist discipline. Students will identify an area of focus, which must be agreed by the programme team to ensure it fits coherently within the overall programme of study and is pitched appropriately for postgraduate-level enquiry. The Independent Project gives the student the opportunity to draw on scholarly literature, professional practice and/or areas of personal academic interest, thus demonstrating advanced critical thinking skills, intellectual independence, professional judgement and effective self-management. It also allows the student to extend their engagement beyond the set curriculum, deepening their expertise and personalising their postgraduate learning experience. In some cases, the content of the Independent Project must be taken from a module missed or failed. The tutor will advise on this.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to complete at postgraduate level. This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning at an advanced level. The topics will relate directly to the student’s home programme by allowing the student to pursue aspects of intellectual or professional interest that connect to their specialist discipline. Students will identify areas of focus, which must be agreed by the programme team to ensure they fit coherently within the overall programme of study and are pitched appropriately for postgraduate-level enquiry. The Independent Project gives the student the opportunity to draw on scholarly literature, professional practice and/or areas of personal academic interest, thus demonstrating advanced critical thinking skills, intellectual independence, professional judgement and effective self-management. It also allows the student to extend their engagement beyond the set curriculum, deepening their expertise and personalising their postgraduate learning experience. In some cases, the content of the Independent Project must be taken from modules missed or failed. The tutor will advise on this.

This studio-based module introduces the fundamentals of architectural design through observation, research, representation and early-stage design development. Students explore how architectural ideas are generated and developed through an iterative process of inquiry, making, testing and reflection. Working at a small architectural scale, students investigate how design responds to context, use and spatial intention. Through drawing, model making and visual research, they analyse architectural precedents and develop skills in communicating design ideas. The module also introduces key design considerations such as site response, user experience and material awareness, while encouraging collaboration, discussion and critical reflection within the architectural studio environment.

Data Science has dominated nearly all industries worldwide today. Various sectors, including banking, agriculture, journalism, and healthcare, utilise data science. This module will review various applications where data science has had a significant impact over the last decade. You will benefit by knowing how some of the leading frameworks in Data Science work while at the same time testing them over real-life datasets. This module aims to develop your awareness of the application areas of data science techniques. It enables you to understand the breadth of the area you are studying and, thereby, the breadth of the area into which you can be employed.

This module provides a comprehensive introduction to machine learning (ML) and deep learning (DL), with emphasis on their real-world applications across different domains. You will learn the foundational and advanced algorithms and gain hands-on experience with frameworks such as Scikit-learn, TensorFlow, or PyTorch. The module integrates theoretical understanding with practical application, preparing you to design, train, evaluate, and deploy machine and deep learning models.

The Systems and Network Security module provides a practical and theoretical understanding of how modern operating systems and computer networks enforce security. It explores how systems manage user privileges, control access to resources, authenticate users, and implement secure communication mechanisms. You will examine how local and network-facing services can be configured, hardened, and monitored to reduce exposure to common attack techniques.
The module introduces key concepts in applied cryptography, secure network design, and the fundamentals of ethical hacking. You will study how attackers identify weaknesses, how protocols can be manipulated, and how controlled penetration testing can be used to assess the resilience of real systems. Through hands-on configuration of virtualised environments, you will learn to analyse network behaviour, apply system hardening methods, and evaluate insecure defaults or misconfigurations.
You will work with tools and techniques used in professional practice, including secure configuration frameworks, packet inspection, access control mechanisms, and service monitoring. The learning in this module maps to CyBOK knowledge areas and draws on industry standard frameworks such as NIST guidance, CIS Controls, and ISO 27001, supporting the development of skills relevant to industry roles and recognised certification domains.
By the end of the module, you will be able to design, implement, and evaluate secure system and network configurations, preparing you for roles in system administration, network defence, security operations, and junior penetration testing.

This module equips students with the ability to integrate AI-driven features into secure and ethical web applications. It combines practical machine learning workflows with foundational and advanced cybersecurity concepts, enabling students to design intelligent systems that are robust, secure, and responsible.
Students gain hands-on experience building AI-enabled web features such as chatbots, recommender systems, and classifiers, while learning how to secure these applications against common vulnerabilities. The module also examines the risks associated with modern AI deployments—such as adversarial attacks, model leakage, and prompt injection—and teaches mitigation strategies aligned with industry best practice.
Ethical, legal, and regulatory considerations are embedded throughout, including fairness, transparency, algorithmic bias, and compliance frameworks (GDPR, CCPA, EU AI Act). By the end of the module, students will be reflective practitioners capable of building secure, trustworthy AI-enhanced systems.
This module directly supports several MSc Computing Programme Learning Outcomes, including critical evaluation of technology, problem-solving, secure software design, ethical responsibility, and the use of advanced tools and frameworks.

This module provides a comprehensive introduction to the principles, structures, and behaviours of modern computer systems. It examines how hardware, operating systems, and networks collaborate to execute programs, manage resources, and enable secure, reliable communication across distributed environments. The module combines theoretical understanding with extensive hands-on experience, enabling students to explore system-level functionality through practical laboratories that utilise Linux, virtual machines, and network analysis tools.
Students develop the foundational systems knowledge required to understand higher-level computing topics such as cybersecurity, cloud infrastructure, software engineering, and artificial intelligence. By engaging with real-world diagnostic and performance-monitoring tasks, students gain the technical fluency and critical insight needed to design, evaluate, and troubleshoot complex computing environments.
Module Context
Computer Systems is a core foundational module within the MSc Computing programme and supports a range of specialist pathways, including software engineering, cybersecurity, cloud computing, and applied AI. The module establishes essential competency in the structure and operation of computing platforms, forming a crucial bridge between low-level system behaviour and the design of robust, scalable applications.
It provides the systems perspective needed to interpret performance issues, assess security vulnerabilities, understand virtualisation and cloud architectures, and reason about the behaviour of distributed or AI-driven systems. The technical and analytical skills developed here underpin many advanced modules and are directly transferable to professional roles in systems engineering, DevOps, IT operations, penetration testing, and infrastructure development.

This module develops advanced knowledge and applied skills in the use of data analytics and artificial intelligence (AI) to support decision-making in engineering and construction projects. It is designed for students without prior experience in computing or advanced mathematics and focuses on the practical interpretation and application of data rather than programming.

The module examines how project data can be structured, analysed and communicated to improve planning, risk management, sustainability assessment and project performance. Students will engage with real world datasets and scenarios, using accessible industry tools to develop insights and support strategic and operational decisions across a range of project contexts.

Through a combination of conceptual understanding and applied learning, students will explore emerging applications of AI and data driven approaches in the built environment, including predictive analytics, digital twins and performance monitoring. The module emphasises critical evaluation of data quality, ethical considerations and the limitations of digital technologies in project environments. Students will consider issues such as data governance and transparency, recognising that expectations and regulatory requirements may differ across jurisdictions and project settings.

The module is part of the MSc Construction Management and Digital Innovation programme and complements other core modules relating to project management and BIM. It equips students with practical data literacy and analytical skills, preparing them to operate in a sector where data driven decision making and AI enabled processes are becoming standard practice.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress.

This module provides an opportunity for students to undertake a project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s home programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus but these must be agreed by the programme team to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress to Level 6.

This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s home programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus but these must be agreed by the programme team to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress.

This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s home programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus but these must be agreed by the programme team to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience. In some cases, the content of the Independent Project must be taken from modules missed or failed. The tutor will advise on this.

In this module, you will explore a range of topics that are essential for your professional development as you begin your career in the Architecture, Engineering, and Construction (AEC) industry. The module introduces you to some of the important roles carried out by professionals in order to create the built environment. You will learn about the typical professional activities, professional code of conduct and explain how these integrate with all stakeholders, processes, and practices in the built environment industry. You will research and discuss the structure of the industry, understanding the construction market and observing the importance of the construction industry to the UK and global economy. The module introduces management theories, stages of development projects, management of design and construction processes and the different organisation structures, sizes and operations within the marketplace. You will explore legal aspects covered within the English legal system, health & safety, quality, environmental systems and the importance of managing Equality, Diversity and Inclusion (EDI) on construction. The lectures will be supported by interactive workshop sessions which will be facilitated by the tutors with industry input where appropriate. You will take part in role play, scenario analysis and research in developing knowledge and understanding. Level 4 modules are designed wherever possible to have a focus on preparing you for university life through various initiatives that foster growth. This module is designed to support you in your transition into Higher Education while developing essential skills to enhance success. There are a number of additional support initiatives which you can engage with, which include induction sessions, academic guidance tutors (AGT), student support coaches, mentoring programmes and various areas of digital support.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress to Level 5.

This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s home programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus and the format for the assignment in consultation with their tutor to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience. In some cases, the content of the Independent Project must be taken from modules missed or failed. The tutor will advise on this.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress to Level 6.

This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus and the format for the assignment in consultation with their tutor to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience. In some cases, the content of the Independent Project must be taken from modules missed or failed. The tutor will advise on this.

The AI Systems Engineering module provides you with a comprehensive understanding of the methodologies, frameworks, and best practices for designing, deploying, and managing AI systems at scale. This module equips students with the practical and theoretical knowledge required to build end-to-end AI solutions that are scalable, reliable, and reproducible across various industries. Through a structured learning approach, students will explore key topics such as data engineering, AI development frameworks, model development, AI deployment strategies, monitoring, and MLOps. The module also incorporates real-world case studies in healthcare and agriculture, allowing students to apply AI system engineering principles to domain-specific challenges. A strong emphasis is placed on Responsible AI, covering ethical considerations, transparency, fairness, and compliance with data privacy regulations. By the end of this module, students will have the technical expertise and critical thinking skills needed to develop and manage AI solutions that adhere to industry standards and best practices. This module is essential for students pursuing careers in AI engineering, MLOps, data science, and AI system architecture, providing them with hands-on experience in tools such as DVC, MLflow, Kubernetes, Docker, TensorFlow Serving, and monitoring frameworks.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress to Level 5.

This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus and the format for the assignment in consultation with their tutor to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience. In some cases, the content of the Independent Project must be taken from modules missed or failed. The tutor will advise on this.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress.

This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus and the format for the assignment in consultation with their tutor to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience. In some cases, the content of the Independent Project must be taken from modules missed or failed. The tutor will advise on this.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress.

This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus and the format for the assignment in consultation with their tutor to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience. In some cases, the content of the Independent Project must be taken from modules missed or failed. The tutor will advise on this.

This module can be taken by students at the discretion of the Programme Leader. It provides flexibility within the student’s home programme to accommodate students who, for example, transfer late into the programme or have exceptional circumstances that mean they could not otherwise attain the necessary credits to progress to Level 6.

This module provides an opportunity for students to undertake an independent project on approved subject-related topics which balances directed and independent learning. The topics will relate directly to the student’s programme by allowing the student to consider aspects of interest to them that relate to the discipline they are studying. Students will choose the areas of focus and the format for the assignment in consultation with their tutor to ensure that they fit coherently to the overall programme of study.

The Independent Project gives the student the opportunity to draw on first-hand experience and/or areas of personal interest, thus demonstrating critical thinking skills, independence, motivation and time management. It also allows the student to go beyond the set syllabus of their degree, thus personalising their learning experience. In some cases, the content of the Independent Project must be taken from modules missed or failed. The tutor will advise on this

This module provides a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML), covering foundational theories, principles, and mathematical underpinnings. You will explore intelligent agents, problem-solving through search techniques, knowledge representation, probabilistic reasoning, and optimisation methods in AI. The second half of the module focuses on machine learning methodologies, including supervised and unsupervised learning, feature engineering, and model evaluation. Through practical implementations, students will develop skills in building intelligent systems, critically evaluating their effectiveness, and applying computational techniques to solve real-world challenges. This module is essential for students pursuing AI-related careers, as it lays the groundwork for more advanced studies in deep learning, generative AI, and Applied AI engineering.

This module explores the theoretical foundations of highway and railway geometric design and construction, with an emphasis on sustainable travel solutions. It equips you with the knowledge and skills required to design transport alignments, including horizontal and vertical geometry. The module builds on Level 5 knowledge from Fluid Mechanics and Soil Mechanics and incorporates aspects of water management in infrastructure design.

A critical aspect of transport design is managing water around infrastructure. The module examines both traditional (grey) drainage solutions and nature-based (blue-green) solutions, which restore water cycles and provide environmental benefits.

Throughout the module, you will engage in practical design exercises, a group transport alignment project, and a feasibility study on drainage systems. Industry guest lectures and site visits will supplement your learning, exposing you to real-world challenges and innovations.

Employability: This module enhances technical skills in transport infrastructure design, problem-solving abilities, and sustainable engineering approaches, aligning with professional roles in civil engineering, transport planning, and water resource management.

The module involves a design project where you are required to conceptualize and design a transport alignment. This project encourages the practical application of theoretical knowledge gained in the module and fosters critical thinking in addressing real-world transportation challenges.

The module also includes the feasibility study of systems to manage water, including both blue-green solutions and grey infrastructure. You will learn to assess the technical, economic, and environmental viability of different solutions.

The module will be delivered through a mix of seminars, workshops, and site visits. Practical design exercises and case studies will be integral to the learning process, allowing you to apply theoretical concepts to real-world transportation and projects. Guest lectures from industry experts will provide additional insights.

Assessment methods include a combination of theoretical understanding, practical design skills, and project-based evaluation. You will be assessed through the comprehensive evaluation of their transport alignment design project and drainage feasibility study and associated design.

Note: To pass this module, Civil Engineering students must achieve a weighted average of 40% or above across all pieces of summative assessment, and a mark of 30% or above in each separate assessment.

This module aims to support you to create a portfolio of evidence that meets the Knowledge, Skills, and Behaviour (KSB) criteria outlined in the standards. You will achieve this through both work-based learning and the academic work submitted at the University. Additionally, you will be required to plan your ongoing professional development through personal development planning and by maintaining a lot of the activities you undertake.

Furthermore, you will learn how to directly apply the theoretical knowledge you gain to real-world scenarios in your workplace. New skills and behaviors that align with your job roles will be developed, facilitating the integration of theoretical knowledge with practical application, ensuring clear connections between what is learned in theory and how competencies are demonstrated in the workplace.

This will be achieved through blended learning, providing a tailored, personalised and flexible approach to your learning experience.

This module will not carry any credits and will be assessed on a pass/fail criterion.

The module offers an in-depth exploration into the advanced behaviours of materials. The primary objective is to develop a comprehensive understanding of material innovations and introduce you to methods for assessing embodied carbon and sustainability in the context of materials choice. Building on the foundational knowledge gained in the earlier module in Civil Engineering Materials and Soils, this module considers advanced concepts to allow you to make sophisticated decisions about materials for Civil Engineering projects.

In addition to material behaviours, you will be introduced to cutting-edge material innovations, including advanced composites, smart materials, and nanotechnology. You will also be encouraged to foster an awareness of emerging materials that push the boundaries of traditional construction materials, providing new possibilities for structural design and performance.

You will be equipped with the skills to assess the embodied carbon and sustainability implications associated with different materials choices. You will also explore life cycle assessment methods to evaluate the environmental impact of materials throughout their life cycle, from extraction to disposal.

The module is designed to align with contemporary industry practices in materials selection and sustainability assessment. The incorporation of real-world case studies ensures that you are prepared to make informed decisions that balance performance, innovation, and sustainability in civil engineering projects.

The module will be delivered through a combination of lectures, seminars, and workshop/laboratory sessions. Practical exercises, case studies, and exposure to industry practices will provide you with hands-on experience in assessing and selecting materials based on advanced behaviours and sustainability criteria.

You will be assessed through technical reports that involve the application of materials selection to real-world scenarios with sustainability criteria.

Note: To pass this module, Civil Engineering students must achieve a weighted average of 50% or above across all pieces of summative assessment, and a mark of 40% or above in each separate assessment.

The module is aimed at developing understanding of vibration in structures, and gives you the skills required in using analytical and numerical assessment techniques with a focus on methods of damping and seismic design. You will develop a deep understanding of vibration phenomena in structures; skills in employing both theoretical and computational methods to predict and evaluate the dynamic response of structures; and skills in seismic analysis and design codes to ensure structural resilience in seismic-prone regions. Building upon foundational knowledge from level 5 and Level 6 modules in structures, this module ensures a progressive and in-depth understanding of dynamic behaviour in structures. The module will also cover structural forensics in relation to measuring real-time stresses and strains, structural responses and condition.
Practical exercises and case studies will be integral to the learning process, allowing you to apply advanced theoretical concepts to real-world structural dynamics and earthquake engineering challenges. The incorporation of these practical exercises ensures that you gain hands-on experience, preparing you for challenges encountered in the field of civil engineering, particularly in seismically active regions.
This module develops transferrable skills crucial for careers in structural engineering, earthquake resilience design, and infrastructure assessment. You will gain expertise in seismic code compliance, structural monitoring techniques, and the use of advanced computational tools such as finite element analysis software (e.g., ANSYS, SAP2000). These skills are directly applicable to roles in structural consultancy firms, disaster risk management organizations, and research institutions specializing in earthquake engineering.
In addition to in-class tests, you will be assessed through a project that involves the application of advanced structural dynamics and earthquake engineering principles to real-world scenarios.
Note: To pass this module, Civil Engineering students must achieve a weighted average of 50% or above across all pieces of summative assessment, and a mark of 40% or above in each separate assessment.

This module will develop knowledge and understanding of how sustainable and emerging technologies are transforming the design, production and management processes of buildings to ensure that these buildings are energy efficient, resilient to climate change and contributing to UN sustainable development goals. You will explore and evaluate options for sustainable design and production technologies and management for future buildings. The design aspects will include green and passive design, renewable energy systems, water conservation and choice of sustainable materials. The production options will include the use of design for manufacturing and prefabrication, 3D printing and robotics and automation. You will consider whole life cycle performance of buildings, and you will analyse operational and production control decisions relating to planning, health and safety, quality and other key factors and the relationship between maintenance requirements, materials, and sustainability considerations. You are expected to use or relate to the environmental assessment tools to justify their selected sustainability strategies. This module will use, if possible, a live building project provided by a construction, architecture or property development company and guest lectures / workshops to inform the innovative solutions that have been or should be considered for realising sustainable building. You will be challenged to think about the use of emerging technologies for future proofing the built environment.

This module introduces the core principles that underpin the management of complex projects in construction, civil engineering and infrastructure contexts. It provides a critical foundation in project lifecycles, organisational structures, financial frameworks and leadership challenges, enabling students to understand how major built environment and engineering projects are conceived, structured and delivered. Students will examine established and emerging project management methodologies, considering how different governance models, procurement environments, stakeholder dynamics and risk conditions influence decision-making across the project lifecycle. The module explores the strategic and organisational dimensions of projects, including the financial and commercial factors that shape project viability, performance and value. Teaching and learning are practice-oriented, drawing on case studies and scenarios from construction, civil engineering and infrastructure sectors. Through applied exercises, discussions and problem-based activities, students will engage with realistic project situations and develop their ability to evaluate options, justify decisions and respond to the complexity and uncertainty inherent in construction and engineering projects. The knowledge and capabilities developed in this module reflect core employability skills sought by employers. These skills provide a strong foundation for a wide range of project-based roles and enhance students’ readiness for professional practice. By the end of the module, students will have developed a strategic understanding of how projects are structured and governed within built environment and engineering contexts and the leadership and decision-making capabilities required to manage complex projects in professional practice.

Algorithms explores the areas of algorithmic design, algorithmic analysis, and algorithmic choice. The module starts by considering simple numerical algorithms (mean, mode, etc.), and fundamental data structures such as arrays, lists, and dictionaries to refresh ideas taught in Software Development 1 and Software Development 2. The main body of the module focuses on algorithmic analysis and understanding, examining searching, sorting, and the supporting data structures: stacks, queues, trees, and graphs. The latter part of the module focuses on algorithmic strategies and a further consideration of finite state machines. Algorithms contains a thread of algorithm design running through it, starting with simple algorithm specification, then considering performance characteristics, before ending on common algorithmic design strategies. Students will incorporate ideas presented in the Software Development theme, supplemented by the formal view provided in Mathematics for Computer Science. Algorithms provides the foundational knowledge of the Algorithms and Artificial Intelligence theme within Computer Science. The aim is to ensure students have fluency in algorithms so they can undertake the tasks in the later modules of the Artificial Intelligence and Machine Learning theme. Specifically, the ideas of searching and sorting presented in Algorithms will be returned to in Artificial Intelligence, where these principles will be used to make machine decisions.

This module introduces students from non-computing backgrounds to the fundamentals of software development, providing the skills needed to design, implement, test, and maintain applications. Emphasis is placed on developing practical programming competence, computational thinking, and professional coding practices. By the end of the module, students will be able to confidently produce working software solutions and critically reflect on their design and development process.

The Industrial Placement module allows students to undertake an optional placement in industry. The placement enables you to develop your skills by working in an industrial setting relevant to your programme of study.
The Industrial Placement is a 12-month full-time work placement in industry with graduate-level learning opportunities. If a 12-month placement is not possible, or is cut short, a minimum of 9 months of placement work must be undertaken. The aim of the placement is to apply your degree learning to real-world tasks in the workplace.
As the Industrial Placement is an optional 20 credit module, the credits gained will be excluded when calculating your final degree classification.

The aim of the module is to introduce you to architectural history and theory through modern and contemporary architectural history, theory, and practice, with a particular focus on architectural movements and key architects. You will develop critical thinking, analytical, and communication skills that are essential for both academic study and future employment in architecture and related fields.

Through lectures and seminars, you will be introduced to a selection of significant architectural movements and case studies, learning how to interpret architectural narratives and buildings. This module will develop your ability to research, write critically, and present ideas effectively - key skills for architectural practice, journalism, heritage conservation, and academia.

The module incorporates structured tutorials and group discussions to enhance your learning experience and you will explore architectural topics through both visual and written formats.

On successful completion of this module, you will be able to analyse and understand the basic principles of histories and theories of architecture.

Level 4 modules are designed wherever possible to have a focus on preparing you for university life through various initiatives that foster growth. This module is designed to support you in your transition into Higher Education while developing essential skills to enhance success. There are a number of additional support initiatives which you can engage with, which include induction sessions, academic guidance tutors (AGT), student support coaches, mentoring programmes and various areas of digital support.

The aim of the module is to introduce the foundational principles of statics, dynamics and mathematics for engineering. It explores the different types of stresses that materials undergo and how these materials respond under the influence of such stresses. The module extends its focus to statically determinate structures, and their behaviour under various stress conditions. Additionally, a crucial aspect covered is the concept of structural stability, exploring the factors that contribute to the equilibrium and robustness of structures.

The module places emphasis on the development of conceptual understanding of the physical world, including engineering artefacts and natural environmental processes, through the language of mathematics. It aims to reinforce and extend your understanding of core mathematical concepts used in the solution of engineering problems. You will develop proficiency in mathematical methods critical for engineering analysis and problem-solving. Recognising the pivotal role of quantitative reasoning in engineering, this module is designed to provide you with the necessary tools to analyse, model, and solve engineering problems
Furthermore, the module goes beyond theoretical frameworks and introduces practical considerations by addressing a variety of commonly used structural forms. Both qualitative and quantitative analyses are employed to describe the behaviour of these structures. Emphasis is placed on understanding complex states of stress within solids, and the intricacies of how materials respond when subjected to diverse and challenging stress patterns.

A significant facet of the module involves an exploration of the failure mechanisms inherent in materials. This includes an examination of the failure modes exhibited by both ductile and brittle materials. By scrutinising these failure mechanisms, the module equips you with the knowledge necessary to design structures that not only withstand various stresses but also maintain their integrity and safety over time. The teaching will include real life example of failure. The module serves as a gateway to the understanding of the principles governing the behaviour of structures under different loading conditions, and preparing you for the challenges of structural engineering.

You will learn through lectures, seminars, examples classes, experimental laboratories and practical applications. Students will be assessed through in-class tests and laboratory activities. You will be introduced to risk assessments for safe working practices in laboratories.
This module develops problem-solving skills critical to engineering practice, equipping you with the ability to analyse structural performance and mechanical behaviour. These skills are directly applicable in civil, architectural, and mechanical engineering industries, preparing you for future roles such as structural analyst, site engineer, or technical consultant.

Level 4 modules are designed wherever possible to have a focus on preparing you for university life through various initiatives that foster growth. This module is designed to support you in your transition into Higher Education while developing essential skills to enhance success. There are a number of additional support initiatives which you can engage with, which include induction sessions, academic guidance tutors (AGT), student support coaches, mentoring programmes and various areas of digital support.

Note: To pass this module, Civil Engineering students must achieve a weighted average of 40% or above across all pieces of summative assessment, and a mark of 30% or above in each separate assessment

The Computer Networks and Network Security module develops practical understanding of how computer networks operate and how network-based security controls protect interconnected systems. Building on foundational cyber security knowledge, the module focuses on core networking concepts and the defensive mechanisms used to reduce exposure to common network threats. You will explore the TCP/IP model, IP addressing, routing fundamentals, and the behaviour of common network protocols. The module examines how misconfigurations, insecure protocols, and poor segmentation create vulnerabilities within networked environments. Emphasis is placed on understanding traffic behaviour, identifying weaknesses, and applying appropriate defensive configuration techniques. Through structured lab sessions, students analyse packet captures, configure firewall rules, implement basic segmentation strategies, and evaluate insecure network configurations within controlled virtual environments. The focus is on developing technical confidence in network analysis and defensive configuration rather than advanced penetration testing. The module aligns with CyBOK knowledge areas relating to network security and secure infrastructure principles. It prepares you for progression into more advanced operational modules while supporting development towards entry-level technical roles in network defence and infrastructure support.

The Fundamentals of Cyber Security and Information Protection module provides a structured introduction to core cyber security principles for students transitioning from non-computing backgrounds. It establishes the essential technical foundations required to understand how computing systems operate, how information is protected, and how vulnerabilities can be identified and mitigated. The module begins with an overview of cyber security as a discipline, introducing fundamental concepts such as confidentiality, integrity, availability, authentication, and access control. You will explore how operating systems manage users and permissions, how data is protected, and how security controls are implemented at a system level. A central focus of the module is understanding threats and vulnerabilities. You will examine common attack categories, misconfigurations, and weaknesses that affect digital systems. Introductory concepts in vulnerability assessment and controlled penetration testing are presented to develop awareness of how attackers identify and exploit weaknesses, and how defensive measures are applied in response. The emphasis is on analytical understanding and responsible practice rather than advanced exploitation techniques. Practical lab activities support the development of technical confidence. You will work within controlled virtual environments to analyse basic configurations, identify insecure settings, apply hardening measures, and interpret simple monitoring outputs. Foundational concepts in threat modelling, auditing, and security monitoring are introduced to support structured security thinking. Ethical and legal responsibilities associated with system access, testing, and information protection are embedded throughout the module. Emerging trends in cyber security are discussed to situate foundational knowledge within a dynamic and evolving threat landscape. This module provides the technical and conceptual base necessary for progression into more specialised study in network security, cyber security operations, digital forensics, and cyber risk management.

The Digital Forensics and Incident Response module provides an in-depth exploration of how digital evidence is identified, collected, analysed, and interpreted to support security investigations and post-incident analysis. The emphasis is on the principles, methods, and tools of digital forensics, establishing a strong technical foundation for understanding how digital traces reveal attack patterns, system misuse, or data compromise. You will work through the full forensic lifecycle, from acquisition and preservation of evidence to detailed analysis, interpretation, and reporting, while learning how to maintain evidential integrity and legal admissibility. The module also introduces incident response as a complementary discipline, demonstrating how forensic findings guide containment, eradication, and recovery activities. Through a series of guided investigations and applied case studies, you will learn to reconstruct events, attribute actions, and provide structured, defensible reports suitable for organisational or legal contexts. By the end of this module, you will be equipped to perform comprehensive forensic investigations and contribute effectively to multi-stage incident response operations.

This module introduces you to the core principles and practices of data analytics and visualization, essential for making informed, evidence-based decisions in today’s data-driven world. It covers the full analytics lifecycle—from data wrangling and exploratory analysis to predictive modelling and interactive visual storytelling—while incorporating statistical reasoning and ethical considerations. You will develop hands-on skills using industry-standard tools such as Python visual libraries and will work with real-world datasets across domains including business, social media, and public policy. Through applied tasks and a practical project, you will gain both technical proficiency and the ability to communicate insights clearly to diverse audiences, preparing them for roles in analytics, consultancy, and research.

Development for Data Science Applications introduces you to the fundamental skills required to build simple data-driven applications. The module assumes no prior experience in programming or technical subjects and focuses on developing confidence through hands-on, practical learning. You will learn the basics of programming for data science, including working with data, writing simple scripts, and using widely adopted tools and environments. The module emphasises how code is used to collect, clean, analyse, critically evaluate and present data, enabling students to understand and participate in the development of data-driven solutions. Key topics include structured problem-solving, introductory programming concepts, working with datasets, and developing simple applications such as dashboards or automated data processes. Learning is supported through practical exercises and real-world case studies, ensuring students can immediately apply their skills in contexts such as business, marketing, finance, and public services. The aim of this module is to equip you with the foundational development skills needed to support data science work, collaborate effectively with technical teams, and build simple, functional data applications. By the end of the module, you will be able to design, develop, and explain basic data-driven solutions, even without a prior technical background.

This module introduces students to core concepts in data management alongside the ethical, legal, and regulatory considerations surrounding data use. It is designed to equip students (specifically those from non-computing backgrounds) with the practical skills to design, implement, and deploy relational database systems using SQL, while also exploring the fundamentals of NoSQL databases. Beyond technical competence, the module critically examines the broader impact of technology. It covers key legal frameworks (such as GDPR and data protection laws), professional responsibilities, and ethical theories relevant to data handling, AI, and wider digital practices. Through real-world case studies and critical discussions, students will develop a nuanced understanding of their role in building responsible and accountable technological solutions.

Game Engineering brings together the elements of the BSc Computer Games Programming degree by having you construct a game engine from the elements of your previous work. You will then use the developed game engine to create a game, demonstrating your ability to undertake significant software engineering work, as well as delivering a significant piece of portfolio work. You will work as a team to show your ability to work collaboratively on technical deliverables. The aim of Game Engineering is to develop your confidence in building large-scale software systems (a game engine) in collaboration with a team of other technical students. Building significant software systems is an important skill not only in games development but in software engineering as a whole.

As more corporations continue to migrate their network services cloud environment and seek cloud solutions to leverage its efficiency and cost savings benefit, it is therefore expedient for companies to have staff with an adequate cloud administrative knowledge set. The demand for highly skilled cloud administrators is now greater than ever. This module allows students to be on the leading edge of systems technology in heavily virtualized environments, in an IT niche that will grow as more small and mid-sized companies outsource IT departments.

This module introduces students to the fundamentals of cloud services and applications. It will provide an expansive insight into essential cloud concepts, technologies, protocols, services, and practices that enable businesses to shift information systems from on-premises computing infrastructures to highly scalable internet architecture and the administrative skills to manage deployed cloud services. This module will open students to new cloud adventures as they explore different types of cloud computing models, its security, data management capabilities, compliance, and legal issues through hands-on activities.

Indicative topics include an introduction to various cloud service models, an introduction to virtualisation, Defining and implementing policies for cloud-based systems, open source and vendor-specific solutions on the cloud, network connectivity in the cloud, Introduction to the cloud administrative skills (with emphasis on patches, permissions, and service deployments), vulnerabilities assessment, analyse and storage cloud data, network security, introduction to cloud architectural design, cloud network management, monitor and performance, introduction to multi-core technologies, insight into fix system error and cloud technologies update.

Game Physics covers the fundamental concepts required to create realistic motion within 2D and 3D graphics applications. The module provides the core principles of how a computer can be used to create and model a physics simulation to move objects on screen. This includes understanding the model representation and how it is connected to but differs from the visual representation. The module explores concepts ranging from simple movement and collision detection to simulation of cloth and liquids.

The aim of Game Physics is to develop students’ fluency in computer physics simulation. The module will require students to understand the theory of physical movement (such as core mechanics) and apply the knowledge in how to develop a simulation of a world within the computer. Games Physics forms one of the three core principles of Computer Games Programming alongside Computer Graphics (visual representation) and Artificial Intelligence (realistic behaviour).

Data Visualisation explores the art and science of visual descriptive statistics. The module starts by introducing the principles of data visualisation and the process of visualisation design. Visualisation design then plays an important role throughout the module, as the students are introduced to the perceptual and cognitive foundations of visualisation, and the core visualisation techniques for different types of data. The module concludes by examining how visualisations can be evaluated via user studies and using the results the students gather from these studies in a further data reporting scenario. Data Visualisation also incorporates web development as the interactive visualisations developed will be presented via a web platform. Students will develop their visualisations using a suitable web framework and deploy their visualisations appropriately. The web development aspect will require students to apply both front-end and back-end development processes to present the data stored. Data Visualisation provides the capstone to the core Data theme in Computer Science. It builds on the statistical techniques and data presentation ideas provided in Data Science. The module allows students to present the results processes the techniques of Data Science, considering different delivery scenarios such as business reporting, data journalism, and scientific visualisation. The aim is to ensure students understand how to present their results in both a correct and engaging manner.

This module explores the principles and practices of artificial intelligence (AI) in digital games, focusing on techniques that create engaging, adaptive, and believable gameplay. You will study both classical AI methods and modern approaches tailored to interactive environments. Topics include pathfinding and navigation, decision-making systems, behaviour modelling, procedural content generation, and adaptive difficulty. The course emphasizes practical implementation: you will build AI agents and integrate them into small game prototypes, learning how to balance technical efficiency with the design goals of fun, fairness, and immersion.

This module provides you with foundational knowledge and practical skills to conduct professional digital investigations in a variety of contexts. It introduces the principal of cyber forensics, providing technical, legal, and ethical foundations of digital forensics, while developing core competencies in evidence acquisition, forensic analysis, and reporting. You will work with tools such as Autopsy, FTK Imager, Wireshark, Jadx and Volatility to examine digital artefacts across multiple platforms including Windows, Linux, and Android. Through hands-on lab activities, you will examine different file types, file systems, metadata, logs, network files and volatile memory and respond to incident scenarios. The module incorporates international standards such as ISO/IEC 27037 and aligns with the National Cyber Security Centre (NCSC) guidelines and the Cyber Body of Knowledge (CyBOK). This module adopts a workshop-centred teaching and learning approach, where you will collaborate in a small group during lab sessions. This strategy blends practical exercises, problem-based technical challenges, and bite-sized lectures, all enriched by group discussions and guided independent study. To enhance engagement and deepen understanding, students will complete pre-workshop preparation through flipped learning elements, including short videos, learning resources (e.g., O'Reilly), and game-style quizzes via Moodle. Through real-world case studies and group practical exercises you will gain core understanding and implementing digital forensic process and understanding the complexities of incident response activities.

This module significantly advances your software development skills, focusing on the design and implementation of complex software systems. You will take a model-driven approach throughout, integrating Object-Oriented Programming (OOP), Unified Modelling Language (UML), and software design patterns to effectively bridge conceptual modelling and practical development. You'll deepen your understanding of OOP principles, including abstraction, encapsulation, inheritance, and polymorphism, through hands-on Java programming. You will learn to capture requirements and design robust systems using UML diagrams such as Use Case, Class, Sequence, State Machine, Activity, Component, and Deployment diagrams. The module also introduces model-based testing, enabling you to validate UML models against their Java implementations. You will gain proficiency in applying design patterns (creational, structural, and behavioral), understand their architectural implications, and employ them within the Model-View-Controller (MVC) framework. You'll use modern component-based frameworks to understand code reuse and integrate event-driven programming techniques to develop graphical user interfaces (GUI) using best design practices. Throughout the module, emphasis is placed on best coding practices, testing and quality assurance using JUnit, and integrating emerging technologies such as AI into modern software development workflows. You will gain comprehensive knowledge of robust system design, architecture, and industry-standard practices. This, combined with the analytical precision and advanced problem-solving methods taught, prepares you for advanced technology roles or further academic study.

This module builds upon foundational computing knowledge to develop technical competencies in networks and operating systems. You will gain understanding of the infrastructure that underpins modern digital environments, cloud services, and enterprise IT operations. The module emphasises both theoretical principles and practical implementation skills essential for professional IT practice. Building on introductory computing concepts from Level 4, this module is delivered through integrated theoretical instruction and extensive hands-on laboratory work. You will develop professional-level skills in network design, configuration, and management, alongside comprehensive understanding of operating system architecture, administration, and security hardening. The module prepares you to address complex real-world challenges in enterprise IT environments and positions you for advanced study in specialised areas such as cloud computing, cybersecurity, and systems engineering. Upon completing this module, you will be equipped with technical knowledge and practical competencies to: • Apply networking concepts, including routing protocols, VLAN configuration, network segmentation, and Quality of Service (QoS) mechanisms to real-world network design challenges • Design, deploy, configure, and manage network infrastructure and secure LANs • Demonstrate professional fluency in command-line operations and scripting for automated system and network administration across multiple operating system platforms • Understand and manage advanced operating system functionalities, including process scheduling, memory management techniques, file system architectures, and storage virtualisation • Install, configure, update, and maintain operating systems environments, performing file system management, user administration, and service configuration tasks • Systematically troubleshoot network and operating system issues using industry-standard diagnostic tools, methodologies, and best practices • Implement and manage system security frameworks, including access control mechanisms, firewall configurations, intrusion detection systems, and security hardening procedures • Proactively assess and mitigate network security risks through vulnerability analysis, and security auditing practices • Apply current industry practices in virtualisation and containerisation technologies to deploy, manage, and optimise systems Developing competence in these concepts provides important foundational knowledge in network architecture, systems administration, cyber security principles, and virtualisation technologies. This technical foundation supports progression to Level 6 modules whilst contributing to preparation for careers in Network Engineering, Systems Administration, Cloud Engineering, Cyber security Operations, and IT Infrastructure Management.

Cyber-Security explores the risks and mitigations inherent to computer use. The module incorporates ideas from ethical practice, risk management, legal considerations, and technology-based solutions to address computer security issues. Cyber-Security begins by examining the concept of privacy from a philosophical, legal, and ethical stand-point, before exploring some of the technology used to protect an individual’s privacy. The module then continues by introducing foundational principles of computer security, including policies, legal frameworks, CIA (Confidentiality, Integrity, Availability), threats, and attacks. With these principles in place, the module explores secure design and the use of cryptography in computer systems. Finally, human-factors, including interface design and governance are explored. Cyber-Security brings together concepts covered in a range of modules throughout computing, including Computing and Society, Software Development 2, and Databases. Cyber-Security explores how the issues introduced in other modules fit within current computer security definitions. The module also explores the technology to support computer security throughout. The module will require students to undertake evaluation of systems to understand vulnerabilities and mitigations. This will best place students to understand the requirements of security as they enter the workplace.

Software development and programming form the foundation of all Computer Science studies, from web development to artificial intelligence. This module introduces you to the main concepts of computational thinking and their translation into the fundamentals of programming. You will learn to create pseudocode and Python programs while exploring how programming languages provide essential resources such as documentation, libraries, integrated development environments (IDEs), and debugging tools. The emphasis will be on core programming principles rather than language-specific details; however, Python will be the primary language for class examples, laboratory exercises, and coursework submissions. Python has been chosen for its popularity with employers, widespread use, and its syntax being particularly suitable for novice learners. The module is designed to future-proof your skills and provide a solid foundation in programming for the remainder of your studies. In addition to technical skills, the module supports you in developing key academic and professional competencies for computing, including finding, evaluating, and using technical information, becoming resourceful, and building resilience as an independent problem-solver. You will also be introduced to the use and integration of artificial intelligence and AI-based tools in programming. These skills will help you transition effectively into Higher Education and develop the mindset of a computer scientist. Indicative Content • Understanding and applying decomposition, pattern recognition, and abstraction. • Learning the syntax, semantics, and structure of Python, including good coding practices. • Developing, testing, and debugging simple programs using core programming constructs. • Translating problems into subproblems and pseudocode before coding. • Using documentation, libraries, and project management tools effectively. • Exploring the ethical and effective use of AI tools (e.g., GitHub Copilot, ChatGPT) to support programming. Student progress is supported in the module via online lecturer resources, online coding practice and assessment platforms that support our in-person teaching via seminar and lab activities. These activities are centered on well-defined tasks that are supported in the classroom by lecturers and lab demonstrators.

This module explores more advanced structural analysis techniques. The primary aim is to cultivate the necessary knowledge, understanding, and skills to analyse and solve complex problems associated with multi-variable structural systems. This includes an in-depth focus on both statically determinate and indeterminate structures, with an extended emphasis on the analysis of plates. Emphasis is placed on the application of theoretical knowledge to real-world engineering problems. You will engage in practical problem-solving exercises, case studies, and a design project that requires the application of advanced structural analysis techniques to address complex engineering challenges. The module introduces you to the Finite Element Method (FEM), a powerful numerical technique widely used in structural engineering. You will not only understand the theoretical foundations of FEM but will also gain practical experience through the use of finite element analysis software, preparing them for sophisticated analysis and design tasks. The module also extends your knowledge to include structural dynamics. The module also covers design processes for foundations, retaining walls, and slopes. The primary objective is to equip you with in-depth knowledge and skills essential for designing resilient, effective and stable support systems within the broader context of civil engineering projects. This module builds upon knowledge acquired in earlier modules, specifically the Level 5 structures and soil mechanics modules. You will learn to design and implement appropriate foundation types based on site-specific conditions and project requirements. You will also gain insights into the principles governing the stability and performance of retaining structures, mitigating potential failures, and designing structures and slopes that meet safety and performance criteria. Eurocode 7 (or the latest version if relevant) will be used as the basis for the module. The module is designed to align academic knowledge with industry practices, preparing you for the challenges encountered in the field of civil engineering. The incorporation of practical design exercises ensures that you develop the skills necessary for designing geotechnical structures in a professional setting. In addition to technical proficiency, the module fosters transferable skills such as teamwork, problem-solving, and effective communication through collaborative design projects and group problem-solving exercises. These skills are essential for success in engineering consultancy and professional practice.

This module develops students’ understanding of structural principles, sustainable construction strategies, and technical detailing within an integrated architectural context. Working on a small to mid-size building project, students explore how structure, materials, and environmental considerations influence architectural and technical design decisions. The module introduces key structural systems, construction materials, and building components, focusing on load paths, stability, and buildability. Sustainable construction is considered through material selection, durability, resource efficiency, and embodied carbon awareness. Through lectures, workshops and project-based learning, students develop and communicate technical design solutions using drawings, models and digital tools, strengthening their ability to integrate architectural intent with technical design.

The aim of this module is to provide you with a comprehensive understanding of materials used in civil engineering and construction. The emphasis is on knowledge and understanding of the physical properties and embodied carbon in materials including environmental and sustainable considerations relating to their source, manufacture, use and disposal. Delving into the composition and properties of a diverse array of materials, the module offers an holistic exploration of the building blocks that form the backbone of construction practices with an awareness of the environmental impact.

You are introduced to the characteristics of various materials, ranging from traditional and modern materials through modern materials to minerals, rocks, and geological structures. The exploration extends beyond a surface-level understanding, aiming to provide students with appreciation of how each material contributes to the structural and functional aspects of civil engineering projects while considering their environmental footprint.

A significant component of the module involves hands-on experience through testing procedures, where you will actively engage in experiments to evaluate the properties of materials. Importantly, sustainability metrics are integrated into these evaluations, ensuring that you gain insights into the environmental impact and life cycle considerations of the materials that you study.

Moreover, the module goes beyond the static understanding of materials, considering their dynamic nature during construction processes. Emphasis is placed on the workability of materials in their finished state, with a focus on sustainable construction practices. This involves accounting for the challenges and considerations associated with the utilization of materials in real-world construction scenarios, fostering an understanding of how choices made in material selection and applications can contribute to sustainable and environmentally responsible engineering practices. By intertwining sustainability principles with the study of materials, this module equips you to make informed decisions that prioritize both structural integrity and environmental consciousness in the realm of civil engineering and construction.

You will learn through lectures, seminars, examples classes, experimental laboratories and practical applications and will be assessed through project and laboratory activities. You will be introduced to risk assessments for safe working practices in laboratories.
This module develops key technical and analytical skills required in the civil engineering industry. Through laboratory testing and material selection exercises, you will gain practical experience in evaluating construction materials, an essential competency for careers in structural design, geotechnical engineering, and sustainable construction. The emphasis on environmental impact assessment will also prepare you for roles in sustainability-focused engineering fields. Additionally, the module fosters problem-solving and critical thinking abilities that are highly valued in both engineering consultancy and research sectors.
Level 4 modules are designed wherever possible to have a focus on preparing you for university life through various initiatives that foster growth. This module is designed to support you in your transition into Higher Education while developing essential skills to enhance success. There are a number of additional support initiatives which you can engage with, which include induction sessions, academic guidance tutors (AGT), student support coaches, mentoring programmes and various areas of digital support.

Note: To pass this module, Civil Engineering students must achieve a weighted average of 40% or above across all pieces of summative assessment, and a mark of 30% or above in each separate assessment.

This module requires you to work on a contemporary research project which strikes a balance between academic research and real-world problem-solving, ensuring you will develop the qualitative and quantitative research skills needed for the industry, whilst also improving communication skills and the use of technology. Instead of a traditional dissertation, you will develop a research-led project the findings for which are engaging, accessible, and applicable to industry settings. There are three options for this research project: Option A: Consultancy Focused Project You will work on an industry defined brief (actual or simulated). You will adopt a consultancy stance, scoping the problem and proposing solutions. You are required to apply for the brief you prefer, explaining why you are interested in the topic. Outputs for this option are: • Strategic proposal and reflective log • Presentation Option B: Entrepreneurial Focused Project You will propose an entrepreneurial capstone project, either refining a business idea or developing a spin-off concept from the ‘Management of Engineering Innovation’ module, after submitting a short pitch for approval. Outputs for this option are: • Strategic report and reflective log • Presentation Option C: Applied Research Project You will choose a topic relating to an industry challenge from a list of topics, after submitting a narrative explaining why you are interested in the topic. Outputs for this option are: • Technical report and reflective log presentation.

This module introduces Computer Science as a professional and academic discipline. You will learn the fundamentals of computer systems and networks and gain practical skills that will be essential for your future in academia and industry. You will develop and apply your knowledge and skills through a series of practical 'challenges'. Through guided activities, you will be able to recognise and understand the building blocks of the computer-based systems that are prevalent today. Practical skills are complemented by industry case studies through which you will identify and analyse the social, legal, ethical, and environmental impact of computing. You will have the opportunity to develop your skills and knowledge through activities including: • Using the command line interface. • Installing an open-source operating system. • Creating wired and wireless Local Area Networks (LANs). • Troubleshooting connected devices, including camera and sound modules. • Identifying and understanding the fundamental components of a computer (e.g., RAM, CPU, storage). • Undertaking performance measurement and benchmarking. • Developing your awareness of cyber security and the foundations of computer systems, including logic and assembly languages. You will also investigate industry case studies, through which you will gain a breadth of understanding of the place of computer-based systems in industry and society and how professionals can influence issues such as environmental sustainability, equality and diversity, and the global economy.

AI implementation and impact in Software Engineering explores the various AI tools and frameworks which are commonly used in software engineering area. The module focuses on understanding differences between general methods and AI tools in software engineering domain to bridging the skill gap, understand the Ethical and responsible of AI in software development and expand students’ knowledge and problem-solving skills on AI-driven tasks in real world cases.

In this module, students can expect to have insight on few representative AI tools/frameworks, clearly understand the pros and cons of them and gain the insight of ethical and responsible of using them for cases, the ability to choose proper tools to facilitate their work to achieve high efficiency solutions.

This module aims to support you to create a portfolio of evidence that meets the Knowledge, Skills, and Behaviour (KSB) criteria outlined in the standards. You will achieve this through both work-based learning and the academic work submitted at the University. Additionally, you will be required to plan your ongoing professional development through personal development planning and by maintaining a lot of the activities you undertake. Furthermore, you will learn how to directly apply the theoretical knowledge you gain to real-world scenarios in your workplace. New skills and behaviors that align with your job roles will be developed, facilitating the integration of theoretical knowledge with practical application, ensuring clear connections between what is learned in theory and how competencies are demonstrated in the workplace. This will be achieved through blended learning, providing a tailored, personalised and flexible approach to your learning experience This module will not carry any credits and will be assessed on a pass/fail criterion.

As engineering professionals, you will need to integrate sustainability into your decision making process and this module will equip you with the knowledge, analytical tools and critical thinking skills necessary to assess and implement sustainable engineering solutions. You will explore core sustainability concepts, including the triple bottom line, life cycle assessments (LCAs), and environmental impact assessments (EIAs), as well as practical applications in areas such as low-carbon materials, renewable energy, sustainable water management, and circular economy principles. Emphasis is placed on standards and certification systems (eg BREEAM, LEED, Passivhaus), regulatory frameworks, and industry best practices. By critically evaluating the economic, social, and environmental impacts of engineering projects, you will develop the ability to assess sustainability performance using established methodologies and propose alternative solutions that enhance environmental outcomes. You will also examine the future of sustainability, with the increasing impact of climate change and inevitability of the increase in regulation, anticipating emerging challenges and the role of engineers in shaping a more sustainable world.

This module aims to support you to create a portfolio of evidence that meets the Knowledge, Skills, and Behaviors (KSB) criteria outlined in the standards. You will achieve this through both work-based learning and the academic work submitted at the University. Additionally, you will be required to plan your ongoing professional development through personal development planning and by maintaining a log of the activities you undertake. Furthermore, you will learn how to directly apply the theoretical knowledge you gain to real-world scenarios in your workplace. New skills and behaviors that align with your job roles will be developed, facilitating the integration of theoretical knowledge with practical application, ensuring clear connections between what is learned in theory and how competencies are demonstrated in the workplace. This will be achieved through blended learning, providing a tailored, personalised and flexible approach to your learning experience This module will not carry any credits and will be assessed on a pass/fail criterion. For the level 4 apprenticeship programme such as the Construction Site Supervisor apprenticeship, this module supports the preparation of your portfolio for the End Point Assessment set by the standard.

This module has three distinct component parts: land surveying, drawings, and measurement. Through hands-on experience with professional surveying equipment and real-world fieldwork applications, you will develop industry-relevant competencies required in construction management, civil engineering, and building surveying roles. In the first component, you will gain practical knowledge of surveying instruments used in industry, learning to conduct surveys, interpret results, and apply mathematical techniques such as trigonometry and coordinate geometry. By working in teams, you will simulate real-life surveying tasks, improving your ability to work collaboratively on-site, a key employability skill for surveying and construction professionals. The second component develops your technical drawing abilities, both manual and digital (CAD, GIS, 2D/3D modelling), enabling you to create and interpret technical plans used in engineering and architecture. These skills are highly sought after in design, construction, and infrastructure projects. The third component focuses on quantity measurement and costing, crucial for building surveyors and construction managers. You will learn to perform take-offs from drawings, apply measurement conventions, and use digital tools for managing construction information, such as BIM (Building Information Modelling). This module prepares you for future careers in the built environment sector, enhancing problem-solving, digital proficiency, teamwork, and analytical thinking, all of which are essential for professional success. Level 4 modules are designed wherever possible to have a focus on preparing you for university life through various initiatives that foster growth. This module is designed to support you in your transition into Higher Education while developing essential skills to enhance success. There are a number of additional support initiatives which you can engage with, which include induction sessions, academic guidance tutors (AGT), student support coaches, mentoring programmes and various areas of digital support. Note: To pass this module, Civil Engineering students must achieve a weighted average of 40% or above across all pieces of summative assessment, and a mark of 30% or above in each separate assessment.

In this module, you will explore fundamental theories and concepts of project management in construction. Construction projects are complex and provide challenges in managing resources mainly people, plant and materials, specialist subcontractors effectively. You are introduced to contemporary principles and concepts in project management and the processes, tools and methodologies that are utilised to complete the construction projects successfully are explored. The relationship of project management with strategic objectives of the client organisation, quality, health and safety, risk management are covered. You will be introduced to time cost relationships and techniques of progress monitoring of the projects including the use of Building Information Modelling. You will develop critical project management skills, including leadership, risk management, and stakeholder communication, preparing you for careers in construction, architecture, and infrastructure development. The module also considers the role of project management in delivering sustainable outcomes and supporting organisational commitments to environmental and social responsibility. By completing this module, you will develop skills in project planning, leadership, risk management, and contractual negotiation. These competencies are essential for careers in construction management, quantity surveying, architectural technology, and project consultancy. You will also enhance your ability to use digital tools such as BIM, which are increasingly required by employers in the built environment sector.

This module explores the dual paradigms of natural and computational intelligence by integrating theoretical insights with practical applications. It examines the biological inspirations behind intelligent behaviour and contrasts these with computational approaches based on algorithmic design and computability. Topics include the foundational paradigms of AI, cellular and developmental systems, evolutionary computation and algorithms, as well as behavioural, collective, and swarm intelligence, culminating in the study of hybrid systems that merge natural and computational methodologies. The course is designed to provide students with a comprehensive understanding of how bio-inspired techniques can be applied to solve complex, multidisciplinary challenges, while addressing issues of computational efficiency, system feasibility, and the trade-offs inherent in AI system design. This module is carefully structured to ensure that students not only gain theoretical insights but also develop practical and analytical skills necessary for advancing the field of AI through a synthesis of natural and computational approaches.

Data Visualisation explores the art and science of visual descriptive statistics. The module starts by introducing the principles of data visualisation and the process of visualisation design. Visualisation design then plays an important role throughout the module, as the students are introduced to the perceptual and cognitive foundations of visualisation, and the core visualisation techniques for different types of data. The module concludes by examining how visualisations can be evaluated via user studies and using the results the students gather from these studies in a further data reporting scenario. Data Visualisation also incorporates web development as the interactive visualisations developed will be presented via a web platform. Students will develop their visualisations using a suitable web framework and deploy their visualisations appropriately. The web development aspect will require students to apply both front-end and back-end development processes to present the data stored. Data Visualisation provides the capstone to the core Data theme in Computer Science. It builds on the statistical techniques and data presentation ideas provided in Data Science. The module allows students to present the results processes the techniques of Data Science, considering different delivery scenarios such as business reporting, data journalism, and scientific visualisation. The aim is to ensure students understand how to present their results in both a correct and engaging manner.

Designing, building, deploying, and maintaining secure software in digitally connected societies, is notoriously challenging. Software development projects are typically driven by commercial motivations, in which features, and functionality are prioritised at the expense of security. However, given a scenario in which an exploit is compromised and results in detrimental consequences (e.g., financial loss, reputational damage), it is not uncommon for the priority of security to be rapidly elevated. This module introduces students to concepts, knowledge, and applied principles of "security by design", that aims to mitigate such scenarios. In this module, students will utilise Secure Software Development Lifecycle (SSDL) frameworks to investigate and apply recommended practices for eliciting requirements, designing solutions, as well as developing, testing, implementing, and maintaining secure software applications and systems.

Cloud computing offers numerous benefits for organisations, in terms of their operational computing requirements. Cloud services are typically flexible and scalable; provide high availability and performance and are charged within “pay-as-you-utilise” pricing models. However, as the adoption of cloud computing continues to grow, organisations and their associated consumers have become increasingly popular targets for malicious actors, who aim to exfiltrate information, deploy malware, and find opportunities for criminal activities amongst many other motivations. In this module students will acquire an extensive insight to cloud principles and concepts, data asset management and protection, IAM, vulnerability management, implementing security controls, detecting, responding to, and recovering from incidents. Indicative details include shared security responsibility, least privilege, defence in depth, threat actors, diagrams, trust boundaries, cloud delivery models, regulatory requirements, tagging cloud resources, protecting data in the cloud.

The Final-Year project allows students to explore a topic of their choosing based on their own interests as agreed and supported via a member of the academic team. The project provides an opportunity for students to research and deliver a significant piece of individual work that incorporates the practical and analytical skills presented in their programme. The Final-Year project will enable students to explore a topic of their choice. There are four project-types planned: •Student-defined. •Academic-defined (research-based). •Industry-defined. •Social enterprise. All projects will be signed-off by an academic supervisor. The students’ goal is to produce a product and supporting report. A final-year project showcase with external partners will finalise the module.

Concurrent and Parallel Systems covers the aspects of developing applications that utilise available hardware to improve overall performance. Starting initially by looking at multithreading and how we can build applications that are executing more than one operation on a single CPU, the module will further explore how we can exploit multi-core processors and how we control such systems.

The module then explores using multiple computers to solve larger problems, focusing on how computers communicate and coordinate to ensure consistent results in parallel application scenarios. Technologies such as Message Passing Interface (MPI) and cluster computing shall be investigated.

The module concludes by exploring General Purpose Graphics Processing Unit (GPGPU) programming, using a suitable framework and API to exploit graphics card hardware to solve general problems.

Deep learning is a machine learning technique that teaches machines by example. Deep learning is a key technology behind driverless cars, voice control devices, disease early detection, investment modelling, among others. Deep learning achieves recognition accuracy at higher levels than ever before. This module will present students with a series of real-life deep learning applications. At the same time, it provides them with a solid foundation to start collaborating in related industries. This module recalls Machine Learning concepts to explain the fundamental models behind several deep learning applications. The deep learning applications module aims to remark the importance of this paradigm in our lives whilst providing students with the tools to understand its science.