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Course summary

This course has been created to deliver a skill set and knowledge base in “multimodal” and “big data” analysis techniques, which are a recognised scarcity within UK Life sciences. You will receive world-class training in core statistical, machine learning and computational methodology, and you will have the opportunity to apply your skills to real-life settings facilitated by the world-leading Institute of Psychiatry, Psychology & Neuroscience. The course will apply to a broad spectrum of graduates preparing for a career in medical statistics and health informatics, or professional methodologists and clinical researchers working in the private or public health sector. This course is also suitable if you are a graduate in/work in the fields of computer science, maths, physics, engineering and natural science, including psychology and medicine. The course will prepare participants for the ever-growing need for a sound scientific approach to processing information and generating knowledge in modern health services. Practical skills will be taught through applications to real-life settings in a world-leading research institution in mental health

Entry requirements

A bachelor’s degree with 2:1 honours in Computer Science, Mathematics, Statistics, Physics, Natural Sciences, Electronic Engineering, Psychology or Geographic Information Systems. In order to meet the academic entry requirements for this programme you should have a minimum 2:1 undergraduate degree with a final mark of at least 60% or above in the UK marking scheme. If you are still studying you should be achieving an average of at least 60% or above in the UK marking scheme.

Fees and funding

Tuition fees

EU £4250 Year 1
England £4250 Year 1
Northern Ireland £4250 Year 1
Scotland £4250 Year 1
Wales £4250 Year 1
International £8500 Year 1

Additional fee information

No additional fees or cost information has been supplied for this course, please contact the provider directly.
Applied Statistical Modelling & Health Informatics at King's College London, University of London - UCAS