Applications of Artificial Intelligence

Artificial intelligence (AI) is a broad area of research that uses rigorous and hands-on computational techniques to address significant problems that arise in many different disciplines, including, but not limited to, computing systems, economics, business, healthcare, games, medicine design, education and agriculture. With the rapid advance of AI, there is a growing demand for students who can understand and promote AI to all these sectors.

Our MSc Applications of Artificial Intelligence conversion course will equip you with a skillset on AI techniques, and prepare you for meeting demand, regardless of your academic background. You will obtain a comprehensive perspective of the current developments, the needs and the potential of AI, by participating in taught modules that promote a deep understanding of AI methods together with others that deliver the necessary technical expertise.

Our course will cover areas including:

- Machine learning

- Data mining

- Decision making

- Big data

Our course will give you both theoretical and technical relevant skills, and will offer you:

- the understanding of the specifics and the intricacies of AI methodologies

- the ability to apply both basic and advanced AI methods

- the ability to design and implement novel solutions

You will also gain transferable skills such as the ability to develop and present arguments, as well as the ability to work independently and in groups. Within our School of Computer Science and Electronic Engineering lies the very strong AI for Decision Making research group, which will offer graduates of the course networking opportunities.

The course is developed in collaboration with industry partners and public sector organisations, offering you paid work placement opportunities. Our partners include BT, Profusion, Essex County Council, Essex Police, and Suffolk County Council.

This course is available to study starting in January or October. Part-time study is only available as part of the October-start variant.