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Professional training

The Department of Biostatistics & Health Informatics is a leader in the education of methodology, applied statistics and health informatics. The Department offers a wide range of introductory and advanced training and our statisticians and health informaticians provide consultation on a wide variety of topics related to the field through our Biostatistics & Health Informatics Executive Education Programme. 

Courses include:

  • Introduction to Statistical Programming
  • Practical Statistics for Public Health Research
  • Health Informatics - a Data Science Focused Short Course
  • Introduction to R
  • Introduction to STATA
  • Multilevel and Longitudinal Modelling
  • Prediction Modelling
  • Contemporary Psychometrics
  • Clinical Trials: Conduct and Analysis

Prediction Modelling short course

The Prediction Modelling course is designed to provide a comprehensive introduction to the fundamentals of clinical prediction modelling using modern statistical modelling techniques for health research. It will cover all steps of developing and accessing a prediction model. Computer based teaching introduces students to the theory and practical implementation of cutting-edge predictive statistical and machine learning modelling techniques using the R statistical software.

Discover the BHI advisory service

We provide a Biostatistics & Health Informatics Advisory Service to staff and students, offering initial project advice and technical support with carrying out a research project.

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Innovation Scholars Programme: Health data science

Within King’s "Innovation Scholar" programme, we are providing online training in large data analysis techniques in modern health research. The modules encompass statistical programming, data science, modelling, natural language processing, and other relevant themes. This training will provide flexible and modular pathways for skill development, catering to researchers and healthcare professionals at various career stages, skill levels, and sectors within health sciences.

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