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Artificial Intelligence (AI) BSc

Study of mathematics, statistics, finance, and risk management in real-world contexts.

YOUR PERSONALITY MIGHT BE:

Technically brilliant

Innovative thinker

Problem-solver

Future-focused

POPULAR CAREER FIELDS

Technology & Startups

Research & Academia

Healthcare & Public Health

Finance & Banking

Is this for you?

Artificial Intelligence (AI) BSc

Is this for you?

WHAT IS IT?

Study of mathematics, statistics, finance, and risk management in real-world contexts.

CAREER OPTIONS

CURRENT APPRENTICESHIPS, INTERNSHIPS & WORKPLACES

Internships
Internships
Apprenticeships
Apprenticeships
Works placements
Uni Open Days
Programming for AI on a computer screen.

FIND OUT MORE

About the Course

  • What Is an Artificial Intelligence Degree?


    Artificial Intelligence (AI) is the study of how to make machines think, learn, and act intelligently. It combines computer science, mathematics, and data analysis to create systems that can solve problems, recognise patterns, and make decisions.


    Why Study AI?


    AI is transforming industries, from healthcare and transport to finance and entertainment. Studying AI gives you the skills to design and build intelligent systems that shape the future, whether you want to work on robotics, data science, or ethical technology.

  • Most AI degrees cover:


    • Programming and software development

    • Machine learning and data science

    • Mathematics and statistics for AI

    • Neural networks and deep learning

    • Natural language processing (NLP)

    • Robotics and computer vision

    • Ethics and responsible AI


    Later in your course, you can usually specialise,  for example, in healthcare AI, human–computer interaction, or autonomous systems.



    Degree Types


    • BSc (Bachelor of Science): Focuses on technical, mathematical, and applied AI skills.

    • MEng or Integrated Master’s: A four-year course offering deeper research and design experience in AI systems.

  • Machine Learning Techniques – building models that learn from data using algorithms like regression, trees, and neural networks.


    Programming & Automation – writing AI-driven software using Python, Java, or similar languages.


    Data Handling & Processing – preparing, transforming, and analysing large datasets for AI applications.


    Algorithm Design – creating intelligent systems for search, optimisation, pattern recognition, and decision-making.


    AI Ethics & Evaluation – understanding fairness, bias, accountability, and responsible use of AI systems.

  • A-levels or equivalent including Maths. Computer Science, Further Maths, Physics, or Computing are beneficial and sometimes preferred.


    • Show your curiosity about technology and intelligent systems.

    • Mention coding, maths, or problem-solving projects you’ve enjoyed.

    • Include online courses, competitions, or independent AI projects (like training a model or exploring ChatGPT).

    • Reflect on the ethical and social impact of AI.

    • Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell – A clear, thoughtful introduction to modern AI.

    • Life 3.0: Being Human in the Age of Artificial Intelligence by Max Tegmark – Explores how AI could change our future.

    • The Master Algorithm by Pedro Domingos – Explains how machine learning is transforming technology and society.

    • Hello World: How to Be Human in the Age of the Machine by Hannah Fry – A witty, real-world look at how algorithms shape our lives.

    • Explore different AI degree options and compare course modules.

    • Attend university open days or virtual events to meet lecturers and students.

    • Try online AI or data science courses to see if you enjoy the subject.

    • Read about how AI is shaping the future in fields like healthcare, education, and creativity.

    • AI Engineering - AI engineer, machine learning engineer, deep learning engineer

    • Machine Learning - Machine learning engineer, ML researcher, algorithm developer

    • Data Science - Data scientist, AI data scientist, analytics engineer

    • AI Research - AI researcher, research scientist, academic researcher

    • Robotics - Robotics engineer, autonomous systems engineer, robotics software developer

    • Quantitative Finance - Quantitative analyst, algorithmic trader, financial ML engineer

    • Healthcare AI - Healthcare AI specialist, medical AI developer, clinical AI researcher

    • NLP Engineering - Natural language processing engineer, conversational AI developer, chatbot engineer

    • Autonomous Vehicles - Autonomous vehicles engineer, self-driving car engineer, perception engineer

    • Computer Vision - Computer vision engineer, image recognition specialist, visual AI developer

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