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.
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.
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.
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.
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 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 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 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.
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 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 rigorous foundation in the principles, architectures, and methodologies that underpin contemporary AI systems. It is designed to develop the conceptual, analytical, and technical competencies required for postgraduate study and professional practice in the design, development, deployment, and evaluation of AI systems. Throughout the module, you will engage critically with key areas of AI systems engineering, including system architectures, data and model pipelines, experimentation, deployment, scalability, monitoring, and responsible AI. Teaching combines lectures, analytical discussion, case-based inquiry, and practice-oriented project work. The module places particular emphasis on connecting theoretical principles with real-world AI engineering practice. Through this integrated approach, students will develop advanced skills in analysing system requirements, designing robust AI solutions, evaluating technical and operational performance, and considering the wider socio-technical, ethical, and professional implications of deploying AI systems in practice.
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 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 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 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
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
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.
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.
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.
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.
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.
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.
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).
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 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.
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 provides a rigorous foundation in the principles, paradigms, and methodologies that underpin computational intelligence. It is designed to develop the conceptual, analytical, and technical competencies required for postgraduate study and professional practice in the design, implementation, and evaluation of intelligent computational systems. Throughout the module, you will engage critically with key areas of computational intelligence, including natural and bio-inspired computation, evolutionary computation, cellular and developmental systems, behavioural systems, collective intelligence, swarm intelligence, and hybrid computational approaches. Teaching combines lectures, analytical discussion, case-based inquiry, and practice-oriented project work. The module places particular emphasis on understanding the relationship between natural and computational forms of intelligence and on applying bio-inspired and adaptive techniques to complex problem-solving. Through this integrated approach, students will develop advanced skills in analysing computational paradigms, designing and implementing intelligent solutions, evaluating their performance and applicability, and considering computational efficiency, system feasibility, and the trade-offs involved in intelligent system design.
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.