Engineering with Artificial Intelligence

If you're building the future, you need to know how to protect it. You’ll explore cyber incidents and threats, digital defences, and secure system design — all through the lens of modern engineering and AI.

You’ll learn how attackers think, what makes systems vulnerable, and how to build security in from the basics. Using professional tools, you’ll investigate real-world threats and secure AI-integrated systems.

Through hands-on exercises, simulations, and projects, you’ll analyse attacks and create systems that can stand up to them. Alongside the technical work, you’ll tackle the ethical and legal challenges that come with protecting data and people.

It’s about more than just code - it’s about making smart systems safe for the real world.

Understand how engineering systems communicate is crucial to unleashing the power of AI. You’ll dive into the essentials of networking: protocols, architecture, data transmission, and wireless systems.

You’ll build and test communication setups that support smart technologies like sensor networks and automated systems. Using appropriate tools, you’ll simulate networks, trace data flow, and troubleshoot real-world issues.

You’ll also examine how to secure, scale, and optimise these systems, while tackling the ethical and legal challenges of connected technologies.

This is about building the invisible systems that keep intelligent technologies running and making sure they run right.

Ready to turn messy data into smart decisions? Here, you’ll take on the role of a data detective diving into real industrial data to uncover insights, spot patterns, and build intelligent tools that work.

You’ll get to grips with cleaning and shaping raw data so it tells a clear visual story. Then you’ll explore machine learning in action — training models, testing outcomes, and figuring out how systems can learn and improve. It’s all about building practical skills through hands-on tasks and real-world case studies.

You'll explore the full spectrum of machine learning, from visualising complex data with tools like heatmaps and correlation plots, to training intelligent algorithms that learn from data, recognise patterns, and predict future behaviour with real-world impact. And it’s not just about the tech — you’ll also tackle the big questions around ethics, sustainability, bias, and data privacy. Just because a system can make an informed decision, doesn’t mean it should.

By the end, you’ll be able to take an industrial dataset, turn it into a story, and pitch your findings with clarity and confidence. You'll also learn from the past using real examples of where AI failed - analysing what went wrong, and how it could've been avoided.

It’s fast-paced, relevant, and right at the intersection of data, technology, and impact.

Ecological Structures gives you an opportunity to work like a professional engineer, analysing, testing, and pitching solutions to a real-world challenge. You’ll take on the role of a consultancy team, tackling a project brief that pulls together structural analysis, thermodynamics, and environmental impact. Think things like Electric Vehicle (EV) chassis design or modular building systems - the technology that shapes tomorrow’s world.

You’ll get hands-on with advanced tools like finite element analysis (FEA) to test how your structure performs under stress and explore how heat flows through your design. Then you’ll dig deep into the sustainability side, using Life Cycle Assessment to weigh up the impact of your materials and choices from start to finish.

This isn’t just about getting the maths right — though you’ll do that too. It’s about thinking smart, solving complex problems, and finding ways to make your design adaptable, efficient, effective, and environmentally responsible. Every week you’ll build your skills through focused sessions and use them straight away on your project. It’s collaborative, technical, and built to give you the experience that matters.

This is where your ideas meet action. You’ll immerse yourself in a team project with a real-world brief designing a product, system, or process that solves a genuine challenge. It’s not just about what you build it’s how you plan, research, test, and deliver something that works.

You’ll dig into how research fuels innovation. That means learning how to ask the right questions, gather evidence, and build a strong case for your solution. You'll plan your project, manage change, deal with setbacks, and learn how to keep things moving when everything gets messy, just like in real engineering.

Every decision you make will need backing whether it’s technical, ethical, environmental or commercial. You’ll use design thinking, experiment with prototypes, and learn how to turn a great concept into something real. Alongside your team project, you’ll also develop your own proposal for a new idea that could be taken to market. It’s your chance to explore what matters to you and how you’d bring it to life.

You’ll come away with experience in research, leadership, business modelling, and creative problem-solving. By the end, you won’t just be talking about innovation, you’ll be driving it.

Here’s where machines learn to see and you learn how to make it happen. You’ll explore how vision systems power smart tech in engineering, from spotting defects on a production line to guiding autonomous robots through complex environments.

You’ll work with smart tools to build your own machine vision system. That means data acquisition, processing images, extracting features, training AI models, and evaluating how well your system performs. Research deep learning techniques and understand how visual data can be turned into reliable decisions.

Through hands-on projects and case studies, you’ll design, implement, and refine a solution to a real engineering task. You’ll reflect on the bigger picture: how machine vision affects industry, society, and ethics. This is your chance to build something intelligent, visual, and impactful and to learn what it takes to bring vision to machines.

This is where everything you’ve learned about AI gets put to work. You’ll take on a full data science project from sourcing a dataset to deploying a working model — all built to solve a real engineering challenge.

You’ll dive deep into advanced AI tools and techniques, including deep learning, reinforcement learning, and optimisation. You’ll design, train, and test models that aim to make engineering systems smarter, more efficient and productive.

It’s hands-on and practical. You’ll build AI models with real impact, tackling complex problems and evaluating how your solution performs, where it falls short, and how it could improve. You’ll also create a ‘model card’ to reflect on the limitations and ethical dimensions of your work, making sure your solutions are not just smart, but responsible too.

Along the way, you’ll explore the wider impact of AI on society, the environment, and engineering itself.

This is about applying AI with purpose — turning complex data into real-world results.

This is about leading change using cutting-edge tech to rethink how engineering systems work. You’ll learn how to design and deliver digital transformation strategies that actually get results, using tools like AI, big data analytics, cloud platforms, and secure communication systems.

You’ll explore what transformation really looks like in the real world. That means working with technologies like IoT, digital twins, and scalable software and figuring out how they come together to boost performance, streamline operations and spark innovation.

This experience isn’t just about understanding the tools, it’s about using them strategically. You’ll build a full transformation plan for a specific engineering sector, showing how to integrate AI, manage change, and lead implementation with a focus on impact and ethics.

You’ll be thinking critically about how digital solutions should be built and why it all matters not just technically, but socially and professionally too.

If you're ready to lead engineering into the digital age, this is your launchpad.

This is where data becomes power. You’ll learn how to work with massive datasets to solve real engineering problems, processing information at scale, pulling out what matters, and using it to drive smarter decisions.

You’ll get hands-on with digital tools using them to build data analytics systems that don’t just handle size, but deliver results. You’ll explore machine learning techniques, distributed computing, and visualisation strategies that turn overwhelming information into clear insight.

Working on real-world projects, you’ll collect and process data, build scalable solutions, and integrate AI to optimise engineering systems. You’ll focus on efficiency, sustainability and performance, while also considering the ethical and societal impact of what you're building.

This is where code meets real-world engineering. You’ll design and build software that doesn’t just run, it solves problems. Whether it’s connecting with AI models, powering smart devices, or supporting industrial systems, you’ll learn how to make it work and make it count.

You’ll cover the full development cycle: planning, designing, testing, and deploying software. You’ll explore UI/UX design, APIs, version control, and cloud platforms all while focusing on creating robust, scalable apps built for engineering solutions.

You’ll work as part of a development team, tackling a software project from the ground up. That means integrating AI models, debugging your work, and understanding how it works, why it works, and how it could evolve.

This is your chance to take the lead. You’ll design, manage, and deliver a project of your own something rooted in your degree, relevant to industry, and shaped by your interests.

You’ll be in charge from start to finish: defining the problem, planning your approach, applying technical skills, and producing a full written report. It’s a deep dive into real engineering work guided by a supervisor, but driven by you.

Expect to develop skills in everything from research, planning, development to hands-on technical skills depending on your project. You’ll meet with your supervisor at key checkpoints to review progress, get feedback, and make sure your project stays on track.

Culminating with a final report and a viva, where you’ll present your work and defend your decisions. Along the way, you’ll build serious skills in project management, evaluation, communication, and independent problem-solving, all documented in your portfolio.

It’s your final-year project and your biggest opportunity to show what you’re capable of.