A young female university student working at a dual-monitor workstation displaying neural network visualizations and machine learning code, with a robotic arm on the desk and server racks visible through glass walls, representing the cutting-edge environment of Artificial Intelligence degrees

DEGREE GUIDE

Artificial Intelligence

What do Artificial Intelligence degrees involve?

Artificial Intelligence degrees teach you how to design and develop intelligent systems that can learn, adapt, and solve complex problems. You will explore key areas such as machine learning, robotics, data science, neural networks, and computer vision. These courses help you develop strong programming, analytical, and problem-solving skills while understanding the ethical and societal impact of AI. You will also learn how to work with large datasets, train AI models, and apply AI to real-world challenges in industries like healthcare, finance, and technology. Many degrees offer hands-on projects, industry collaborations, and research opportunities, giving you the expertise to innovate in this fast-evolving field.

Example
Modules

Machine Learning: Explore how computers use data to recognise patterns, make predictions and improve over time without being directly programmed.

Neural Networks: Study how layered systems of interconnected nodes simulate brain function, powering applications like image recognition and speech analysis.

Natural Language Processing: Learn how machines analyse, understand and generate human language for tools like chatbots, translation and sentiment detection.

Common Degree Names

💼 Many courses offer a placement year in industry or research.
🌍 Study abroad is available at some universities.

BSc (Hons) Artificial Intelligence
BSc (Hons) Computer Science (Artificial Intelligence)
BEng (Hons) Artificial Intelligence and Robotics
BSc (Hons) Data Science and Artificial Intelligence
BSc (Hons) Artificial Intelligence and Psychology
MSci Artificial Intelligence
MEng Computing (Artificial Intelligence)

BSc and BEng are both common in this field. BSc focuses more on software and theory, while BEng may include robotics and systems engineering. MSci and MEng are four-year integrated Master’s degrees that include advanced AI study.

A laptop displaying a neural network architecture diagram alongside a small wheeled robot, algorithm sketches and a Python for AI textbook, illustrating the machine learning and robotics skills developed in Artificial Intelligence degrees

Level 3 (A-level / IB Diploma (HL) / Scottish Highers)

AI degrees teach you how to build intelligent systems that can learn, reason, and solve problems. Most courses are technically demanding and require strong mathematical and computational skills.

You'll need:

Maths – essential for all AI courses

Subjects that could strengthen your application:

Computer Science – strongly preferred for programming and algorithms
Further Maths (or IB AA HL) or Statistics – valuable for theoretical or data-heavy courses
Physics – helpful for logic, modelling, and quantitative thinking

✨ Maths is essential. Adding Computer Science keeps the widest range of AI courses open for you. Evidence of coding experience (even self-taught) really helps.

Universities may also accept:

BTEC Extended Diplomas in Computing (being phased out), IT (being phased out), or Applied Science (being phased out). A-level Mathematics is required alongside
BTEC National Extended Certificates or National Diplomas alongside A-levels that meet the subject requirements above
T-Level in Digital Software Development may require A-Level Maths alongside
IB Career-related Programme (IBCP) with Maths at Higher Level among your IB subjects (minimum two, ideally three), alongside your Career-Related Study; a Computing or IT pathway would be directly relevant

AI courses differ in emphasis (theory, software engineering, data science, robotics), so always check each university’s website for the exact subjects and entry criteria.

Level 2 Qualifications (GCSE / MYP / National 5)

Most courses ask for:

GCSE English Language and Maths at grade 4/C or above, or equivalents such as National 5s or MYP

📘 GCSE Computer Science (or equivalent) is useful but not essential; strong Maths skills are particularly important.

💬 Interviews

Formal interviews aren't usually part of the application process. However, some universities may invite you for a short conversation, either online or in person, to learn more about your interest in the subject.

📝 Admissions Tests

Most courses don't require a test, but if you're applying to Imperial for Computing (Artificial Intelligence and Machine Learning), you'll need to sit the TMUA (Test of Mathematics for University Admission). It tests mathematical thinking and reasoning to assess your readiness for the course.

💻 Portfolio / Projects

A formal portfolio isn't required, but reflecting on your coding projects, GitHub work, apps, Kaggle notebooks, robotics or competition entries in your personal statement can strengthen your application and demonstrate genuine interest.

✨ Personal Statement Tips

What draws you to AI - is it machine learning, robotics, natural language processing, computer vision, or something else? Being specific helps, because AI is a broad field with many directions. If you've experimented with coding, built projects, completed online courses, or explored how AI systems work, reflect on what you learned and what questions it raised. But technical experience isn't everything; reading about how AI is changing industries, listening to debates about its implications, or thinking critically about both the potential and the risks shows you're engaging with the bigger picture. Admissions tutors want to see curiosity about how intelligent systems work and awareness that AI raises important questions beyond the technical.

If your qualifications don't match the usual entry requirements, there are some other possibilities.

🌱 Foundation Year in Computing, Science or Data Science

Many universities offer a foundation year if you don't have the required Maths or Computing background. This adds an extra year but leads directly into the full degree.

🎓 Access to HE Diploma (Computing, Science or Engineering)

Accepted by many universities. Make sure your course includes programming and maths or statistics content, and aim for strong results in your graded units.

💼 Level 3 Apprenticeships

Apprenticeships such as Software Development Technician, Data Technician or Digital Support Technician carry UCAS tariff points from 2026 and can support a university application, particularly when combined with a foundation year.

Is this degree right for you?

Members can explore whether this degree fits who they are:

Skills you'd develop and whether they match your strengths
How this aligns with your interests, motivators and values
Career paths and where graduates end up

Start Your Journey → £3 a month

Full access to all self-discovery tools and guides. Cancel anytime.

Skills you would develop in X degree

Skill Name

Context sentence

Heading 6

I'm a paragraph. Click here to add your own text and edit me. It's easy.

Heading 6

I'm a paragraph. Click here to add your own text and edit me. It's easy.

custom skills note goes here

Is this a good fit for you?

Use the tabs to explore the kind of person that this would be a good fit for. Do you share the Interests, Motivations, Values, Work identity and skills that people who thrive in this course tend to have?

Not sure what these things are? Explore your Identity Tree with us first.

Interests that connect well with an Artificial Intelligence degree

Students who enjoy this degree often share these interests. You don't need to feel strongly about all of them, and interests develop over time. If one or two catch your curiosity, or sound like something you'd like to know more about, that's a good sign.

Technology, Computing & Digital Systems: The degree is about building intelligent systems. You'll learn to program, design algorithms, and understand how computing technology enables machines to learn, reason, and interact with the world, from image recognition to language understanding.

Mathematics, Patterns & Data: Machine learning is built on finding patterns in data. You'll train models on datasets, build predictive algorithms, and use statistical techniques to teach systems to recognise images, understand text, and make decisions, developing a deep understanding of how data drives intelligent behaviour.

Students who thrive in an Artificial Intelligence degree are often motivated by

Trends and Pattern-Spotting

You're energised by noticing what's changing before others do, whether that's emerging cultural trends, shifts in data, new technologies gaining traction, or patterns in behaviour. You find energy in predicting what's coming next and understanding why things are moving in a particular direction. You're drawn to the signals others overlook, and you'd rather be early to the question than late to the answer.

Intellectual Challenge

You're energised by pushing your mind to its limits, tackling difficult questions, and wrestling with problems that don't have easy answers. You're drawn to work that requires deep concentration and rigorous thinking. The harder the problem, the more satisfying it feels to work through it, and you'd rather be stretched than comfortable. Easy work bores you rather than relaxing you.

Practical Problem-Solving

You're energised by finding fixes to real-life issues, whether they're mechanical, technological, or social. You're motivated by problems you can see, touch, or experience directly, and you get satisfaction from solutions that work in practice, not just in theory. You'd rather build a prototype than write a report about one.

Analysing and Investigating

You're energised by making sense of information, looking for evidence, spotting patterns, and piecing together how things connect. Whether it's pulling apart data, questioning assumptions, or tracing a problem back to its source, you find energy in the process of understanding what's really going on. You'd rather dig into the details than accept things at face value.

Creativity and Innovation

You're energised by the act of creating something new or finding a fresh way to approach a problem. Whether it's designing, writing, building, or experimenting, you feel most alive when you're generating original ideas rather than following established methods. The possibility that something has never been done before excites rather than intimidates you.

Curiosity and Learning

You're energised by the activity of learning itself: diving into a subject you've never explored, watching documentaries, taking apart how something works, or constantly asking "why?" The process of learning gives you energy, not just the outcome. You don't just want the answer; you want to understand how things connect, why they matter, and what's underneath the surface explanation.

What makes Artificial Intelligence click for the students who love it?

The question that grips them is whether a machine can be made to think, and what happens when it can. They are drawn to the demanding problems that come with it, the kind that take everything they have, and they read widely to get there: statistics, neuroscience, cognitive science, philosophy. They enjoy finding patterns in data that others would miss, designing a model and then working out why it behaves the way it does. The field is wide open, with no one sure where it will end up, and that is where they want to be.

These are the skills that students who love this degree tend to enjoy using. You don't need to be great at them already, but if they sound like you, that's a good sign.

Skill Name

Skills that suit this degree

You don't need to be great at these already — but if you enjoy using them or want to get better at them, that's a good sign.

Do you enjoy writing code and building things that work, and want to push that into creating systems that can actually learn and improve on their own?
Do you like thinking logically about how something works — breaking down a problem step by step and reasoning about the best way to solve it?
Do you find it satisfying to tackle problems that don't have an obvious answer — figuring out an approach, testing it, and refining it until it works?
Do you like working with data and experiments — training something, measuring how well it performs, and trying to understand why?

Careers an Artificial Intelligence degree could lead you to

Artificial Intelligence

What do Artificial Intelligence degrees involve?

Example Modules

Common Degree Names

Is this degree right for you?

Skills you would develop in X degree

Skill Name

Heading 6

Heading 6

Is this a good fit for you?

Careers an Artificial Intelligence degree could lead you to

Example
Modules