Bristol Medical School
We’ve grouped the short courses from Bristol Medical School into five themes. Use the links at the bottom of this page to navigate to the other Bristol Medical School short course themes or return to our main training page.
Please note that as courses are provided by Bristol Medical School, you will be taken to the University of Bristol website to complete the booking.
Data analysis
Questionnaire Design, Application and Data Interpretation
University of Bristol
Start date: 27 January 2025
Duration: 3 days
Delivery: Online
Cost: £660
More information
About the course
Questionnaires are widely used for data collection in health research and evaluation. Their design, use and analysis are key to accurate, comprehensive and complete data. This course is an introduction to questionnaire design, application and data interpretation. It will be delivered by researchers and healthcare professionals experienced in developing, conducting and analysing questionnaire-based research for use in health services research and healthcare.
It covers an overview of processes involved in questionnaire development, testing, administration and data management to provide a basic understanding of the key concepts and approaches when using questionnaires to collect healthcare data and measure outcomes.
What this course will cover
- The basic principles of questionnaire design including developing and testing a questionnaire/outcome measure using qualitative and quantitative approaches
- The important aspects and key issues to consider for administering questionnaires and maximising response rates across a range of health care settings
- How to handle questionnaire data
- How to explore and interpret qualitative and quantitative questionnaire data
How to join
Sign up via the University of Bristol Medical School website
Introduction to R
University of Bristol
Start date: 30 January 2025
Duration: 2 days
Delivery: Online
Cost: £330
More information
About the course
R is an open source statistical programming language, created specifically for data analysis. R is extremely versatile and this makes it a popular choice for health researchers. This course aims to introduce R, focusing on providing the starting point needed to exploit R’s huge potential for statistical analysis.
The course is intended for anyone with no previous experience of R, but who wants to use R in their day-to-day work for storing, summarising and analysing data. Previous experience with handling data is therefore required. No previous knowledge of R or of statistical analysis will be assumed.
What this course will cover
- How to implement the basic operations of R
- How to read in data from multiple sources
- Understanding, manipulating and exploring different types of R objects such as vectors, matrices and data frames
- Where to find help about a given command and explore similar commands
- Using R script files to organise R commands
- Using control structures and functions to write robust and reusable code
- Displaying summary statistics and basic plots
- How to download, install and find documentation for additional R libraries
How to join
Please note, there are pre-requisites for enrolling on this course – details can be found on the full course listing linked below.
Sign up via the University of Bristol Medical School website
Introduction to Data Visualisation and Web Applications Using R
University of Bristol
Start date: 3 February 2025
Duration: 2 days
Delivery: Online
Cost: £440
More information
About the course
This course introduces the key aspects of data visualisation using R. It aims to familiarise participants with the wide world of data visualisation tools and techniques used in R for the creation of dynamic, clear and reproducible graphics and research reports.
The course is intended for individuals with an interest in data visualisation, reproducible research and data science. The course topics apply to nearly all areas of quantitative research, but the course is focussed on visual presentation of data rather than statistical analysis methods.
It is assumed participants will have attended the Introduction to R course or have a similar level of experience with R and/or RStudio. This course is not intended for people who have never used R before.
What this course will cover
- Basic and advanced R graphics: creating simple and advanced informative graphics using ‘ggplot2’
- Customising graphs
- How to produce interactive graphs and display them online
- How to us R Markdown to create dynamic reports
- Using R to develop simple web applications to display results or perform an analysis online
How to join
Please note, there are pre-requisites for enrolling on this course – details can be found on the full course listing linked below.
Sign up via the University of Bristol Medical School website
Machine Learning with Omics Data
University of Bristol
Start date: 19 June 2025
Duration: 2 days
Delivery: Online
Cost: £440
More information
About the course
Health research is increasingly turning to high-throughput molecular datasets (also known as ‘omic’ datasets) to discover novel biomarkers of disease risk and outcome. Unfortunately, the size and complexity of these datasets makes them difficult to manage and prone to many pitfalls.
In this course, we introduce you to the latest approaches from data science for interpreting and extracting useful and reliable biomarkers from these challenging datasets. It aims provide:
- An overview of the principles and methods of epidemiology and data science that are relevant to high-throughput omic studies
- The knowledge and skills necessary to design and utilize population-based omic studies to gain insight and to derive robust biomarkers of exposures and health outcomes
Attendees may have a background in epidemiology, genetics, statistics, public health or a clinical speciality. A basic knowledge of epidemiology is required and some understanding of molecular epidemiology terminology and machine learning would be advantageous. Practical knowledge of R is required as students will be processing large omic datasets in practical sessions.
What this course will cover
-
Examples of published omic analyses and models for epidemiological and medical applications
-
Statistical methods for preprocessing, discovering patterns and testing associations in omic datasets
-
Interpreting the biological relevance of omic patterns and associations
-
Estimating the heritability and proportion of variation explained by omic data
-
Approaches from machine learning for deriving reliable omic biomarkers for indexing exposures and predicting health outcomes
-
Application and interpretation of appropriate metrics for evaluating biomarker performance
-
Ethical challenges of developing, interpreting and applying molecular biomarkers
How to join
Please note, there are pre-requisites for enrolling on this course – details can be found on the full course listing linked below.
Sign up via the University of Bristol Medical School website
Essentials of Infectious Disease Modelling and Economic Evaluation
University of Bristol
Start date: 23 June 2025
Duration: 2 days
Delivery: Online
Cost: £440
More information
About the course
Mathematical modelling is an important tool that can be used to understand the dynamics of infectious diseases. This 2-day course aims to cover the essentials of infectious disease modelling including economic evaluation. The course will provide attendees with the ability to start understanding modelling studies and work with modellers.
The course is intended for epidemiologists, public health specialists, policy makers and healthcare professionals who work in the area of infectious diseases (human and animal health).
Although the computer practicals will be in the programming language R, no knowledge of R is assumed.
What this course will cover
- What infectious disease models are and when they can be used
- How to actively collaborate with modellers
- Designing a model
- Simulating a model using the programming language R
- How to interpret basic reproduction numbers
- Criteria for disease control
- The principles of vaccination and herd protection
- Using models for economic evaluation
How to join
Please note, there are pre-requisites for enrolling on this course – details can be found on the full course listing linked below.
Sign up via the University of Bristol Medical School website
Introduction to Rates and Survival Analysis
University of Bristol
Start date: 25 June 2025
Duration: 3 days
Delivery: Online
Cost: £660
More information
About the course
This course introduces the analysis of survival-time outcomes, consisting of the time each person “survives” until some specified event occurs. This course aims to give students:
- A grounding in the theory behind the methods most commonly used to analyse rates and survival-time data
- Extensive hands-on experience of their application in Stata software
The course is intended for researchers and analysts who wish to analyse and understand survival-time data (time to event data). The course focuses on popular methods of analysing these types of data, mainly Poisson and Cox regression.
What this course will cover
- Definition of rates and the relation between risks and rates
- Manipulating person-time data in Stata using the st commands
- Analysis of rates using Mantel-Haenszel methods and Poisson regression
- Splitting follow-up time to allow for exposures that change with time
- Introduction to survival analysis
- Log rank tests and Cox proportional hazards regression
- Testing for proportional hazards and modelling non-proportional hazards
- Survival-time data management
- Choosing between survival analysis methods.
Please note that ‘repeated measures’ analyses, in which multiple events or measurements are recorded in the same person over time, are not covered in this course.
How to join
Please note, there are pre-requisites for enrolling on this course – details can be found on the full course listing linked below.
Sign up via the University of Bristol Medical School website
