Short courses


RADIANCE - Longitudinal Data Preparation and Visualisation for Epidemiological and Social Research

  • 6 hours
  • 0.5 days (self-paced)


This online course is for anyone who needs to prepare longitudinal data for analysis. It will cover the main procedures needed from converting raw longitudinal data to cleaned data that can be readily analysed. Sessions will encompass data preparation, description, and visualisation, with a focus on longitudinal data and real-world data.

This course is specifically designed to enhance knowledge, self-confidence and expertise among researchers who wish to develop their skills in analysing complex longitudinal biosocial data. It makes key concepts and approaches accessible to quantitative researchers from a wide range of disciplines and sectors, with particular emphasis on how these can be practically applied in their work. It is part of the RADIANCE programme, which has been developed by an expert team from UCL and the University of Manchester to offer comprehensive, state-of-the-art longitudinal data science training all in one place.

Who this course is for

This course is aimed at quantitative researchers working with biomedical and social data who wish to use Longitudinal Data Preparation and Visualisation for Epidemiological and Social Research in their research and would like a short introduction to this topic.

Course content

This course provides an insight to the following topics:

  • Importing and merging data 
  • Selecting cases and variables 
  • Reshaping data 
  • Recoding variables (using loops) 
  • Describing data using summary statistics 
  • Creating transition tables 
  • Using graphs for exploratory analysis 

Teaching and structure

The course consists of 2 pre-recorded lectures, 2 computer practicals (in Stata) and solutions.

Participants will need to be familiar with Stata.


A certificate of completion will be available to download once the required activities have been completed.

Learning outcomes

This course will enable participants to:

  • Understand how complex large-scale datasets are structured 
  • Prepare, using syntax files, complex datasets for appropriate statistical analysis by: 
  • Combining multiple datasets, and aggregating/disaggregating data from different files in a relational database 
  • Manipulating, recoding, and computing derived variables 
  • Provide descriptive summary statistics and graphical representations of the data 

Cost and concessions

The standard fee for this course is £100.

A 10% discount is available for UCL students and staff – please email radiance@ucl.ac.uk for details.

Course team

Dr Giorgio Di Gessa

Dr Giorgio Di Gessa

Giorgio is a Lecturer in Data Science at UCL. Giorgio’s area of expertise include regression analysis, longitudinal data analysis, multi-level modelling, and multiple imputations.

Learner reviews

"The course was excellent and very well designed… I wish all universities offered courses so well designed and well carried out like this one."

"I definitely learned some new functions which I am excited to use in my research. I also think the slide deck from the recorded sessions is the BEST all in one source for every important function you need to perform data cleaning, EDA and visualisation. Huge well done and thanks to the module organisers/convenors."

Course information last modified: 22 Feb 2024, 15:39