
Pre-Masters in Information and Computer Science - Continue to Master of Science - Artificial Intelligence
Brunel University, Russell Building, Kingston Lane, Uxbridge, London, United Kingdom
350773
Last updated: 17/04/2025







About Pre-Masters in Information and Computer Science - Continue to Master of Science - Artificial Intelligence
At the postgraduate level, Brunel University London Pathway College provides the highly acclaimed Pre-Master's programme leading to an excellent range of Brunel University London Master programmes in business and management, computing, engineering & design and arts. After successfully completing the programme students will advance to their chosen progression degree.
A postgraduate pathway will give students valuable insight into postgraduate-level studies in the UK. Most importantly, it will equip students with the appropriate knowledge and skills they need to excel in their chosen taught master's degree.
Artificial intelligence (AI) is the scientific study that enables machines to mimic cognitive functions of human mind, such as learning and problem solving. It has enjoyed a resurgence following the advances of computational power, the availability of large amount of data and the development of theoretical understanding.
Built on Brunel's strong international research profile in intelligent data analysis, the aim of Artificial Intelligence MSc course is to provide the students with a solid awareness of the key concepts of artificial intelligence. Students will develop a critical understanding of the state-of-the-art in this area and the practical skills to create value in its applications to business, scientific and social domains.
The programme offers a wide range of study areas that cover data analysis, various intelligent techniques, machine learning, deep learning, data visualisation, and ethics and governance.
In addition, students will have the opportunity to develop a broader set of skills including study skills, research skills, employment skills and capability skills through group projects, guest lectures or workshops from industry, and dissertation projects with industrial collaborations.
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