King's College London

Course Introduction

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.

Description

Our course is to meet the growing need for a graduate training course that focusses on methodological skills to respond to problems of ?big data? of complexes diseases, which is underpinned by strong statistical methodology and real-world application.?

There is an increasing demand for the acquisition, storage, retrieval and use of information within private and public sector institutions engaged in health research. The range of modern medical data is vast, from patient records, genetics, other omics and imaging data, to real-time measures of physiological responses from wearable sensors, smartphone social media use and environmental data. We will provide you with the necessary state-of-the-art statistical modelling and health informatics techniques to manage and evaluate this data.

You will receive training in key methodological techniques underpinning ?big data? acquisition, information retrieval and analysis using prediction modelling and theory driven analyses approaches.

You will benefit from the teaching of world-renowned experts in the field, you will conduct an applied research project and link to statistical and health informatics research groups, such as the causal modelling group, precision medicine and statistical learning, measurement theory, health informatics and natural language processing groups in the Department of Biostatistics and Health Informatics.

Career prospects

Our course will help you to develop your career in the medical research and health sector, including public health service (NHS), pharmaceutical and computer companies, technology start-ups, government agencies as well as academia and other scientific organizations. Knowledge of applied statistical modelling and data science will also open careers in other sectors such as banking, marketing, insurance and consulting. It will also provide a strong foundation for students interested in obtaining a PhD in biostatistics, data science or informatics with an emphasis on applications in health science.

Knowledge of applied statistical modelling and data science will open up careers across sectors. This is the ideal next step if you?re looking to work/already work in industry, commerce, health or academia. The course will also provide a strong foundation for students interested in obtaining a PhD.

Duration & Attendance Qualification Tuition fees Fee type
1 year
Full Time
Postgraduate Certificate - PgCert £4,100 Home Fees
1 year
Full Time
Postgraduate Certificate - PgCert £4,100 European Fees
1 year
Full Time
Postgraduate Certificate - PgCert £9,500 Overseas Fees

Qualifications required:

  • Domestic 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. Candidates who achieved a 2:2 in their undergraduate degree will need to support their application with a one page personal statement and an academic reference addressing their academic and relevant professional achievement. Other degrees or professional qualifications may also be acceptable such as the Graduate diploma of the Royal Statistical Society.
  • International entry requirements: Students can demonstrate their English Language Proficiency with any of the following tests and grades: IELTS (Academic): 6.5 overall with a minimum of 6.0 in each skill; TOEFL IBT: 92 overall, with a minimum 23 in each skill; Cambridge Advanced Certificate (CAE): 176 overall with a minimum of 169 in each skill; Cambridge Certificate of Proficiency in English (CPE): 176 overall with a minimum of 169 in each skill; Pearson Test of English (Academic): 62 overall, with a minimum of 52 in each skill. The tests listed above are valid if they have been taken within the past two years.
  • IELTS score: 6.5
  • TOEFL score: 92