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.
Big data
Genetic Epidemiology
Start date: 11 December 2024
Duration: 5 days (weekdays only ending 17 Dec)
Delivery: Online
Cost: £1100
More information
About the course
Genetic epidemiology examines the effect of genetic variation on a disease or a health-related outcome. Since 2007, genome wide association studies have been widely used to detect associations between genetic variants and a disease or a health-related outcome in populations. It has facilitated a wide range of discoveries in the genetic epidemiology field.
This course aims to provide a grounding in a wide range of cutting-edge genetic epidemiological methods for complex traits. It is intended for Epidemiologists, Statisticians, Molecular biologists, Clinicians and Psychologists.
What this course will cover
- Introduction to genetics (optional pre-course videos)
- Introduction to data types and formats
- Heritability and genetic architecture of complex traits
- Genetic association of complex traits
- Related study designs
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
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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
Introduction to Epidemiology
Start date: 10 February 2025
Duration: 5 days
Delivery: Online
Cost: £1100
More information
About the course
Epidemiology is the study and analysis of the distribution, patterns and determinants of health and disease conditions within populations. It is a cornerstone of clinical and public health.
This course aims to provide a grounding in epidemiological study designs and measures of disease risk used in aetiological epidemiology and health services research. It is intended for clinicians, researchers, public health specialists and other health care professionals who have only a basic understanding of epidemiology.
Prior knowledge of basic medical statistics so that you understand findings published in peer-reviewed medical journals is important.
What this course will cover
- Exposure measurement and measures of disease occurrence
- Measures of exposure effect (e.g., risk and odds ratios)
- Study designs (randomised controlled trials, cohort studies, case-control studies; ecological studies and cross-sectional studies)
- Bias and confounding
- Simple regression and interaction effects
- Sample size calculations
- An introduction to causal inference
- The future of epidemiology
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
Understanding Trusted Research Environments
University of Bristol
Start date: 24 March 2025
Duration: 5 days (half day sessions)
Delivery: Online
Cost: £550
More information
About the course
Trusted Research Environments (TREs) are in many cases now the default pathway to accessing data, representing a step change in how data is accessed for research and introducing new challenges.
This course will introduce some exemplar TREs (e.g. The UK Longitudinal Linkage Collaboration (UK LLC), NHS England TRE and OpenSAFELY) to highlight the different ways TREs function, and some of the strengths and challenges these environments can introduce to research such as the availability of different tools.
We aim to equip researchers with the confidence to work within TREs through awareness of the benefits, challenges and differences that exist across TREs. The course is intended for researchers who want to learn more about conducting research within a TRE.
What this course will cover
- Different approaches to working within TREs
- Insights into the strengths and challenges of different tools that can be used to manipulate data, conduct analyses, and create safe research outputs
- The steps that need to be taken before analysis can be undertaken and once analysis is complete including quality assurance, requesting safe research outputs
- Governance and data standards
- Common approaches to dealing with known challenges
- The importance of patient and public involvement and engagement including fair processing and transparency
- The benefits of developing good practice in documentation not least to support reproducible research
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
Molecular Epidemiology
University of Bristol
Start date: 31 March 2025
Duration: 3 days
Delivery: Online
Cost: £660
More information
About the course
This course enables participants to develop skills for identifying the causes and consequences of molecular variation within population-based studies. It aims to provide participants with:
- An overview of epidemiological principles that are relevant to population-based molecular studies
- The knowledge and skills necessary to design, execute and interpret population-based molecular studies
The course is intended for individuals engaged in population-based studies who wish to incorporate molecular measures of epigenetic marks, gene expression, metabolite presence, protein abundance or genotype into their research.
A basic knowledge of epidemiology is required, and some understanding of genetics terminology is advantageous. Some practical knowledge of R would be helpful. The course includes information on laboratory-based methods, but is aimed at the non-specialist (i.e. those without first-hand lab experience).
What this course will cover
- The various uses of high-throughput molecular data in epidemiology and medicine
- Key considerations in the design of molecular studies
- Practical analysis of molecular data
- Interpreting the biological function some of the most popular molecular data types
- Methods for deriving and evaluating the performance of molecular biomarkers
- Causality of molecular phenotypes
- Critical appraisal of the molecular epidemiological literature
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
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Examples of published omic analyses and models for epidemiological and medical applications
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Statistical methods for preprocessing, discovering patterns and testing associations in omic datasets
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Interpreting the biological relevance of omic patterns and associations
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Estimating the heritability and proportion of variation explained by omic data
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Approaches from machine learning for deriving reliable omic biomarkers for indexing exposures and predicting health outcomes
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Application and interpretation of appropriate metrics for evaluating biomarker performance
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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
