BEng Artificial Intelligence (G164)
2025 entry
Course summary
In this three-year course, you will learn to understand and apply Artificial Intelligence. You'll learn from our world-class researchers as they develop new algorithms and apply AI to innovations in healthcare, finance, environmental modelling, robotics and the technologies of the future.
Today Artificial Intelligence stands at the forefront of technological innovation, encompassing the design and refinement of algorithms that not only exhibit intelligent behavior but also possess the capacity to adapt and learn dynamically from feedback, evidence, and data. Machine learning is at the heart of modern AI and is a rapidly advancing field with an expanding toolbox of new algorithms for modelling, forecasting and classification in complex application domains. This technology has huge transformative potential, providing new avenues for creativity and problem-solving, and helping us to tackle the difficult and urgent social and environmental challenges that define the 21st century. However, it also opens new ethical, philosophical and regulatory issues that must be faced head-on to ensure fairness and to prevent potential harm.
This interdisciplinary Bachelor of Engineering in AI aims to provide a broad and in-depth understanding of modern AI and machine learning, at both applied and foundational levels. You will be taught by experts in AI and machine learning as well as practitioners with extensive experience of applying AI in their domain. You will interact with our industrial partners who will provide insight into the use of AI in sectors including software development, pharmaceutical, energy, Formula One racing, investment and consultancy, and act as stakeholders on projects. Furthermore, you will have an industrial mentor from whom you can gain individual insights and advice during your studies.
The programme will train you to become an adept AI Engineer with extensive hands-on experience and the expertise to apply modern machine learning to diverse application domains including health, robotics, finance, manufacturing and design. You will become responsible problem solvers in AI and machine learning. For this, you will learn how to programme and manage data at scale; you will study the mathematics that underpins AI, so that you can understand its strengths and limitations; you will develop problem-solving skills, by working in teams and individually on challenging open-ended real-world problems; and you will explore the new ethical and legal challenges that AI brings.
When you graduate, you will be ideally placed to play pivotal roles in the AI transformation of our economy and society, ensuring that this new technology is used effectively and with care.
Course structure
Principles of AI (Years 1-2): You will study the core concepts and ideas underpinning AI. We will discuss what it means to be intelligent, and the ethics and morality of AI in society. You'll hear from business and industry experts about how AI is being applied in practice and the specific challenges faced by their sectors.
Programming & Data Engineering (Years 1-2): You will learn about algorithms and how to programme, gain experience using specialist machine-learning tools and packages, and learn how to manage and analyse data at a large scale using the cloud.
The Mathematics of AI (Year 1): Maths is at the heart of AI and you will need a good grounding in the relevant mathematical ideas to understand the strengths and limitations of different machine learning algorithms. Applied linear algebra underpins data representation and optimisation in machine learning; information theory guides and bounds learning; probability and statistics help us to look for patterns and structures in data.
Machine Learning: Algorithms and Architectures (Year 2-3): You'll learn about a variety of modern machine learning approaches such as deep learning and reinforcement learning, so that you understand their foundations and gain experience using them in practice.
Problem Solving and Applications (Years 2-3): You'll train to be AI problem solvers with experience in a diverse range of application domains including robotics, health, finance, manufacturing and design. You will learn problem-solving skills through experience, by working on real-world projects both individually and in teams.
Entry requirements
We accept a wide variety of qualifications and welcome applications from students of all backgrounds. Below is a guide to the typical offers for this course.
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Selection process
- Regulations and codes of conduct we abide by to create a positive environment for learning and achievement are found in the University admissions policies and procedures.
- If applying with extenuating circumstances please see our policy.
- The admissions statement above relates to 2024 entry. The statement for 2025 entry will be available in summer 2024.