Artificial Intelligence

UCAS code: I400

Here's what Anglia Ruskin University says about its Artificial Intelligence course.

Gain practical experience and place yourself at the forefront of technological innovation, with our Artificial Intelligence degree in Cambridge.

• Study in the Silicon Fen, home to Apple, Microsoft, Samsung AI and many more – the perfect opportunity to connect with top employers.

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

• Accredited by BCS and IET and a Cisco Network Academy for over ten years.

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

• Access our AI lab/software packages, Microsoft Azure and VMware IT Academy.

From self-driving cars to chess-playing computers, artificial intelligence (AI) has been shaping our world for some time now. With our BSc (Hons) Artificial Intelligence degree in Cambridge, you’ll explore the science of machine learning and develop the skills to firmly place yourself at the forefront of technological innovation.

Our degree course, accredited by both BCS and The Chartered Institute for IT, and affiliated with IET (The Institution of Engineering and Technology), will help you stand out to employers in a range of industries, both in the UK and overseas. Once you graduate, you’ll be able to register as an Incorporated Engineer and, with further study, you can become a Chartered Engineer.

Our specialist facilities are perfect places to develop practical skills and get experience of working with industry-standard tools, such as VMware IT Academy and Amazon AWS. We encourage collaboration, so you’ll also learn through activities with your peers, and lectures and seminars from industry experts.

During your time at ARU, you’ll also get the opportunity for a placement year in industry which will see you linked with a high-tech hub company in Cambridge, the region and beyond. You’ll build up experience working and make industry contacts to benefit your studies and enhance your long-term career prospects.

Our Artificial Intelligence degree course has been designed with the industry and employers in mind, meaning you have the opportunity to learn the professional skills you’ll need after graduation. The course is supported by our Employers’ Advisory Group, which includes experts from companies like ARM, Redgate, Amazon and Cambridge Spark.

During your time at ARU, you'll work on live brief assignments proposed by companies like Mathworks or Redgate and you will have 12-month access to Pluralsight professional online training courses for programmers, which is included in and guided through the Introduction to Programming module. This gives you enhanced opportunities to experience real-world professional training as part of your academic course.

You’ll learn all about the history of AI, the systems that underpin AI and the advanced algorithms that are employed. To achieve this, you’ll be using the most up-to-date technologies including software packages and hardware infrastructure.

As part of your studies with us, you will be able to access online educational resources from the Intel AI Academy and Amazon AWS Educate programme. Our specialist facilities include a Cisco and AI lab, and we use tools such as Microsoft Azure Dev Tools and VMware IT Academy. We encourage collaboration, so you’ll also learn through activities with your peers, and lectures and seminars from industry experts.

Are you ready to meet the future head on?

Going to university can offer you a series of once-in-a-lifetime opportunities. As part of your course, you could study abroad with one of our short-term Global Experience programmes. Opportunities include summer schools and placements, lasting from one to four weeks and funded by ARU’s UK Turing Scheme grants.

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 Mathematic Techniques for Artificial Intelligence (30 credits)

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 Core modules: 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)

Year 3 Optional modules: Embedded Computing (15 credits) Distributed Programming (15 credits)

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.