University of Cambridge Masters Degrees in Computer Science

The aim of the course is to provide preparation appropriate for undertaking a PhD programme in computer science. Students select five taught modules from a wide range of advanced topics in computer science from networking and systems measurements to category theory, and topics in natural language processing. Read more

Artificial intelligence (AI) technology is rapidly developing and is increasingly being applied across sectors, posing significant ethical and societal challenges. Read more

The MPhil in Data Intensive Science is a 10-month cross-departmental programme in the School of the Physical Sciences which aims to provide education of the highest quality at the master’s level. Read more

The programme is designed to begin to equip students for engineering leadership positions, developing a high level of understanding and skills in photonic and electronic systems, in particular, the fundamentals of the field together with technology, systems and applications knowledge, and some research experience. Read more

This is an 11-month MPhil programme, taught from within our Information Engineering Division, with a unique, joint emphasis on both machine learning and machine intelligence. Read more

Cambridge is a world-leading centre for innovation in electronic patient and clinical trial data. This is underpinned by an extensive and vibrant community of clinicians, researchers, entrepreneurs, and commercial and public sector organisations. Read more

Cambridge is a world leading centre for innovation in electronic patient and clinical trial data. This is underpinned by an extensive and vibrant community of clinicians, researchers, entrepreneurs, and commercial and public sector organisations. Read more

The MPhil in Digital Humanities is directed by Cambridge Digital Humanities, a research centre with links across a wide range of faculties and units at… Read more

The programme aims to equip students with the skills and knowledge to contribute critically and constructively to cross-disciplinary research on AI, data and algorithms and their ethical and societal implications. Read more