Explore the fundamentals and benefits of R for epidemiology
R is a highly versatile and flexible programming language that is well-suited to statistical analysis and data analysis.
On this six-week course from the UK Public Health Rapid Support Team, you’ll learn about the practical benefits of R for epidemiology, and be equipped with the skills to use R confidently and independently in your work.
Use data management techniques such as data cleaning and processing
‘Dirty data’ is a common phenomenon in every field, but is particularly prevalent in the healthcare and medical sectors. Inaccurate patient information, incomplete records, duplications, and system errors culminate to result in messy datasets.
With the help of your educators, you’ll develop data management skills that will enable you to clean and manage messy datasets, as well as reshape and merge them. With these skills, you’ll create clean, accurate, and relevant data for research and analysis.
Discover data visualisation methods for effective data analysis
Data visualisation is a key step in understanding and extracting information from datasets. Through visualisation, you will be able to identify trends, patterns, and outliers within your datasets.
On this course, you’ll learn how to manipulate and summarise your data to structure and simplify it. From there, you’ll be taught methods and approaches to visualise your data successfully, using epicurves, highlighting, and count graphs.
Learn R with the London School of Hygiene and Tropical Medicine experts
The UK Public Health Rapid Support Team is a division of the London School of Hygiene and Tropical Medicine.
This team focuses on responding to disease outbreaks and equipping medical professionals with the tools they need to stop the spread of disease and prioritise public health.
This is an introductory course for epidemiologists, surveillance analysts, statisticians, data scientists and similar professionals who work in surveillance, outbreak response or research areas with little to no previous experience in R.
