Artificial Intelligence

Your future in AI starts here with skills employers demand and connections that launch global tech careers.

Artificial Intelligence is transforming the world, and this accredited degree puts you at the forefront.

At ARU in Cambridge, you’ll master machine learning, neural networks and ethical AI while creating solutions that transform industries. You’ll be surrounded by Europe’s largest tech cluster and gain unrivalled access to industry leaders, internships and cutting-edge resources.

Graduate ready to shape tomorrow in roles spanning AI development, data science and robotics – where creativity meets technology.

Why ARU?

• Study in Cambridge's ‘Silicon Fen’, Europe's largest tech cluster and home to employers such as Apple, Microsoft and Samsung AI.

• Bring the world of work to life through Live Briefs, designed with employers such as Mathworks and Citisoft to give you exposure to ‘real world’ problem-solving.

• Access exclusive online resources from Intel AI Academy, Amazon AWS Educate, Pluralsight, LinkedIn Learning and zyBooks.

• Get hands-on in our AI lab using advanced software packages, Microsoft Azure and VMware IT Academy.

• Study an accredited course, at a university that's been a Cisco Network Academy for over ten years.

This degree opens doors to diverse, high-demand careers as AI development, machine learning engineering and robotics.

You might work on data science projects in fields like business forecasting and digital healthcare. Your technical foundation will also create opportunities in web development, IT systems and digital security.

With industry connections and hands-on experience, you’ll graduate equipped for a future where technology drives every sector.

Course Modules

Year 1

• Introduction to Programming (30 credits)

• Computer Systems (30 credits)

• Computer Modelling and Simulation (15 credits)

• Fundamentals of Artificial Intelligence (15 credits)

• Introduction to Mathematical Techniques for Artificial Intelligence (30 credits)

• Into ARU

Year 2

• Database Design and Implementation (15 credits)

• Software Engineering (30 credits)

• Ruskin Module (15 credits)

• Advanced Analytical Techniques for Artificial Intelligence (15 credits)

• Machine Learning (15 credits)

• Artificial Neural Networks (15 credits)

• Algorithm Analysis and Data Structures (15 credits)

Year 3

• Final Project (30 credits)

• AI Techniques (Fuzzy Logic and Genetic Algorithms) (15 credits)

• Professional Issues: Computing and Society (15 credits)

• Deep Learning (15 credits)

• Cloud Computing (15 credits)

• Image Processing (15 credits)

• Embedded Computing (15 credits) *

• Distributed Programming (15 credits) *

*optional

Modules are assessed through a combination of coursework (coding, reports, logbooks, presentations, group and individual projects) and exams. Indicatively, the amount of coursework and exam is 52% to 48% in year 1 and 72% and 22% in years 2 and 3, with some possible year on year variation.

Professionally accredited courses provide industry-wide recognition of the quality of your qualification.

• BCS - The Chartered Institute for IT
• Engineering and Technology, Institution of