Training courses
Our portfolio of courses has been developed to reflect the needs of learners working in digital health. The course catalogue is still building and we will be updating as new courses become available.
Please note that as courses are provided by a range of institutions, you will be taken to the course provider’s website to complete the booking.
Short courses
An Introduction to Innovation in Healthcare
University of Bath
Start date: Anytime
Duration: 4 weeks (3 hrs per week)
Delivery: Online (delivered via FutureLearn)
Certification: CPD Certified
Cost: See FutureLearn
More information
About the course
Offered by the University of Bath and Health Innovation West of England, this course provides an introduction to innovation in healthcare.
Explore the need for innovation in the healthcare sector: the development, adoption, and spread of innovations as well as barriers to adoption. The course covers essential tools and techniques for healthcare innovation. Experts in the field will guide learners from idea to realisation.
Emphasis is placed on teamwork, collaboration, and cultivating an innovation mindset.
What this course will cover
- Spotting opportunities for innovation
- How to conduct research
- How to generate ideas
- Practical steps involved in developing and testing initiatives
How to join
Quality Improvement in Healthcare: the Case for Change
University of Bath
Start date: Anytime
Duration: 6 weeks (3 hrs per week)
Delivery: Online (delivered via FutureLearn)
Certification: CPD Certified
Cost: See FutureLearn
More information
About the course
Offered by the University of Bath and Health Innovation West of England, this course explores innovative approaches to enhancing the quality of health and care services.
Participants will examine the complexities surrounding quality improvement in these systems. Addressing challenges such as financial constraints, knowledge gaps, regulatory burdens, and professional biases.
The course will provide deep understanding of the benefits of quality improvement for staff and organisations. Learners will gain the confidence to take part in, or lead, quality improvement projects within their organisations.
What this course will cover
- Quality improvement theories and methodologies
- Quality improvement evaluation
- How to engage stakeholders in co-production
- Systems modelling and analytics
How to join
Business Analytics in Practice
University of Bath
Start date: 3 entry points per year (January, May and September)
Duration: 8 weeks (12.5 hrs per week)
Delivery: Online (delivered via Engage)
Certification: MSc (10 Credits)
Cost: £833
More information
About the course
Analytics in Practice focuses on the crossroads between hard computational practice and understanding business context. With this in mind, this unit has been built in collaboration with IBM.
IBM is one of the oldest and most prolific software companies. It has had tremendous impact on the development of computational analytical tools and methods, building its own practical philosophy for how to best apply those tools and methods in solving business problems.
What this course will cover
- Case study analyses, group work, and practical sessions incorporating software solutions from IBM
- Evaluation of trends in analytics such as
- Big Data management
- Data ethics
- Reference architecture
- New and emerging forms of data
How to join
Machine Learning
University of Bath
Start date: 3 entry points per year (January, May and September)
Duration: 8 weeks (12.5 hrs per week)
Delivery: Online (delivered via Engage)
Certification: MSc (10 credits)
Cost: £833
More information
About the course
This unit will support students to use state-of-the-art machine learning methods for leveraging Big Data across multiple business operations. Coursework will assess the selection, use, and implications of machine learning models on business data. This will include a presentation that explains the process to a non-technical audience.
What this course will cover
- How to choose machine learning algorithms based on data types and specific business contexts
- How to develop, evaluate, and improve machine learning models to make predictions or decisions with business implications
- How to estimate the effects of the machine learning models on business operations
- How to apply ethical principles in the collection, conversion, and analysis of data
How to join
Data Mining
University of Bath
Start date: 3 entry points per year (January, May and September)
Duration: 8 weeks (12.5 hrs per week)
Delivery: Online (delivered via Engage)
Certification: MSc (10 credits)
Cost: £833
More information
About the course
This unit will teach students how to discover patterns in data using algorithms. Coursework will cover the selection, use, and interpretation of data mining models. It will also include a business report that explains the work to a non-technical audience. Prospective students will require a basic knowledge of statistics.
What this course will cover
- How to model business challenges as data mining models
- Choosing algorithms to detect unknown rules and patterns within data and infer their business implications
- How to assess the accuracy and precision of the rules and patterns detected
- Clustering, pattern recognition, unsupervised classification, and anomaly detection and their applications to real world data
How to join
Smart Sensing
UWE Bristol
Start date: Entry points from January 2024
Duration: 150 hours (36 in-person, 114 self-directed)
Delivery: In-person lecture series
Certification: CPD Certified (15 credits)
Cost: £1048/£784 (with/without assessment)
More information
About the course
This module on Smart Sensing provides an advanced understanding of sensors and biosensors crucial to the healthcare sector. The module’s focus includes exploring innovative technologies, particularly implantable and wearable sensors.
Learning outcomes encompass:
- Knowledge of state-of-the-art sensors
- Evaluation of biosensor system components
- Assessment of the impact of innovative technologies on healthcare
- Practical design and characterisation of biosensors for diagnostic purposes
By the end of the module, students are expected to design (bio)sensor systems for specific healthcare needs. Delivery consists of a combination of lectures, tutorials, and practical classes.
What this course will cover
- Biosensors
- Biomolecular recognition
- Sample collection
- Nanotechnology-based transduction schemes
- Physical and physiological sensors
- Data analysis
How to join
Multiple Imputation for Missing Data
University of Bristol
Start date: 10 June 2024
Duration: 3 days
Delivery: Online
Certification: No CPD award
Cost: £660
More information
About the course
Missing data are almost inevitable in medical research. This leads to a loss of power and potential bias. Multiple imputation is a widely-used and flexible approach for handling missing data. This 3-day course aims to provide a theoretical and practical introduction to multiple imputation methods for dealing with missing data in straightforward situations.
The course is intended for statisticians, epidemiologists and other researchers who are, or will be, involved in performing statistical analyses of epidemiological datasets with missing data.
Participants should be familiar with standard regression methods for dichotomous and continuous outcomes beyond the basic introductory level, and be familiar with the core concepts of causal diagrams.
Participants should also be familiar with using either Stata or R as the software package for statistical analyses of the data.
What this course will cover
- An introduction to the problems caused by missing data, including when a complete case analysis is likely to result in bias
- An introduction to multiple imputation
- Practical sessions performing multiple imputation, including interactions and non-linear associations as well as simple diagnostic checks
- A practical session on how to present multiple imputation methods and results in journal articles
How to join
Sign up via the University of Bristol Medical School website
Please note, registration for this course closes 2 weeks prior to the course start date. Once the course is full, a waiting list will be created.
No CPD award is included however learners will be able to register for a LEAP certificate upon completion.
Optimising Recruitment to Randomised Controlled Trials
University of Bristol
Start date: 13 June 2024
Duration: 1 day
Delivery: Online
Certification: No CPD award
Cost: £220
More information
About the course
This 1-day course aims to provide an introduction to the challenges of recruiting people to randomised controlled trials (RCTs). It aims to equip attendees with ways of mitigating or overcoming these challenges.
The course draws on evidence generated by the QuinteT research programme, which specialises in optimising recruitment to RCTs. Course content and examples will be drawn primarily from trials set in secondary care hospital settings that span a range of medical specialities.
What this course will cover
- Common organisational and logistic difficulties that can impede recruitment
- The use of screening logs to monitor recruitment, identify issues, and prioritise solutions
- An overview of the concepts of individual and community equipoise, and their implications for recruitment
- Strategies for engaging with patient preferences for or against trial treatments
- The implications of language and terminology on recruitment when discussing RCTs with potential participants
How to join
Sign up via the University of Bristol Medical School website
Please note, registration for this course closes 2 weeks prior to the course start date. Once the course is full, a waiting list will be created.
No CPD award is included however learners will be able to register for a LEAP certificate upon completion.
Essentials of Infectious Disease Modelling and Economic Evaluation
University of Bristol
Start date: 17 June 2024
Duration: 2 days
Delivery: Online
Certification: No CPD award
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
Sign up via the University of Bristol Medical School website
Please note, registration for this course closes 2 weeks prior to the course start date. Once the course is full, a waiting list will be created.
No CPD award is included however learners will be able to register for a LEAP certificate upon completion.
Statistical Methods for Mediation Analysis
University of Bristol
Start date: 24 June 2024
Duration: 2 days
Delivery: Online
Certification: No CPD award
Cost: £440
More information
About the course
Mediation analysis examines what variables may lie on the causal pathway between an exposure and an outcome. Mediation models are useful for:
- Understanding aetiology
- Providing evidence to confirm and refute theory
- Assessing the impact of intervening on a mediator when it is not possible to alter an exposure
This 2-day course aims to provide an understanding of the statistical principles behind, and the practical application of, mediation analyses in epidemiology. It is intended for medical statisticians, and epidemiologists with a quantitative background and knowledge of linear and logistic regression.
What this course will cover
- Traditional and counterfactual approaches to mediation analysis and the assumptions underlying these methods
- An introduction to counterfactual methods to incorporate intermediate confounders
- Stata commands to run models for traditional and counterfactual approaches to mediation analysis
- Stata commands to run models with multiple mediators or intermediate confounders
How to join
Sign up via the University of Bristol Medical School website
Please note, registration for this course closes 2 weeks prior to the course start date. Once the course is full, a waiting list will be created.
No CPD award is included however learners will be able to register for a LEAP certificate upon completion.
Introduction to Rates and Survival Analysis
University of Bristol
Start date: 26 June 2024
Duration: 2.5 days
Delivery: Online
Certification: No CPD award
Cost: £550
More information
About the course
This 2.5-day course introduces the analysis of survival-time outcomes, consisting of the time each person “survives” until some specified event occurs. The 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
It 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
Sign up via the University of Bristol Medical School website
Please note, registration for this course closes 2 weeks prior to the course start date. Once the course is full, a waiting list will be created.
No CPD award is included however learners will be able to register for a LEAP certificate upon completion.
Further Survival Analysis
University of Bristol
Start date: 11 July 2024
Duration: 2 half days
Delivery: Online
Certification: No CPD award
Cost: £220
More information
About the course
Survival analysis, also known as time-to-event analysis, uses duration data to estimate rates of events and associations of time with possible explanatory variables. This 2 day course (delivered over 2 mornings) is intended for medical statisticians.
Applicants should be:
- Competent users of Stata (although code in R will also be made available)
- Familiar with basic survival analysis e.g. Cox models, equivalent to the level taught in the Introduction to Rates and Survival Analysis short course
What this course will cover
- Parametric survival models and how to implement them
- The use of flexible parametric survival models
- An introduction to the concept of competing risks in modelling time-to-event data
How to join
Sign up via the University of Bristol Medical School website
Please note, registration for this course closes 2 weeks prior to the course start date. Once the course is full, a waiting list will be created.
No CPD award is included however learners will be able to register for a LEAP certificate upon completion.
Economic Evaluation Modelling Using R
University of Bristol
Start date: 16 July 2024
Duration: 3 days
Delivery: Online
Certification: No CPD award
Cost: £660
More information
About the course
The R statistical software provides an efficient, flexible, transparent, and extensible tool for building models for economic evaluation in healthcare. It is an increasingly popular alternative to less efficient, generalisable and powerful software such as spreadsheets.
This course aims to teach the use of R for building decision trees, Markov, and semi-Markov models for economic evaluation and value of information analysis.
This 3-day course is intended for anyone undertaking model based cost-effectiveness analyses. Attendees from academia, government, or industry are welcome.
What this course will cover
- An introduction to R using health economic examples
- Decision trees (deterministic and probabilistic and building your own model in R from scratch)
- Advanced topics in R (program flow, input/output, functions)
- Basic and advanced Markov models
- Semi-Markov models with application to oncology
- Value of information analysis
How to join
Sign up via the University of Bristol Medical School website
Please note, registration for this course closes 2 weeks prior to the course start date. Once the course is full, a waiting list will be created.
No CPD award is included however learners will be able to register for a LEAP certificate upon completion.
Foundations Of Health and Wellbeing - Coming soon
University of Bristol
Start date: September 2024
More information
About the course
This module is intended for those with no medical background who are interested in learning about health. It takes a cradle-to-grave approach; from conception and child development through to nervous system pathologies in old age.
Students will engage in hypothetical medical cases, based on real-world scenarios, focusing on how digital technologies can address clinical needs.
The learning approach involves small group case-based learning, facilitating peer learning and interdisciplinary communication. Assessment includes active engagement, participation in discussions, and a choice of presentation format (verbal, video, or report).
What this course will cover
- Physiological processes of the body
- Illnesses, interventions, and explaining clinical issues
- How to critically analyse approaches to improving patient health
- The impact of digital technologies on patient treatment
- How to propose evidence based technical solutions
How to join
Coming soon
Data Driven Decisions for Business Leaders
Somerset Foundation Trust
Currently accepting expressions of interest
More information
About the course
Data can empower decision makers with valuable insights if utilised in the correct way. This one-day course aims to cover not only what a decision is, but when a decision should be made. By completing this course, business leaders will start to consider questions that they ask in a different light. These ‘data-driven decisions’ transcend gut instincts and subjective opinions, meaning new strategies are grounded in empirical evidence and measurable outcomes. Leveraging data in this way can provide a compass to guide organisations towards innovation and success.
What this course will cover
- A high-level overview of some of the benefits data science can bring
- The nuances of hidden bias in questions, when graphs are misleading, and how to set effective milestones
- How to work effectively with data analysts and data scientists
How to join
Data Science for Data Professionals
Somerset Foundation Trust
Currently accepting expressions of interest
More information
About the course
Data Science for Data Professionals is a three-week course designed for people working with data in healthcare. The course will cover a myriad of technical skills and explore ethical considerations surrounding the use of AI and data science. Participants will learn how to ensure effective decision-making by utilizing available data responsibly.
Prospective participants should have experience analysing data and access to datasets. Due to the fast-paced nature of the course, potential applicants should have a project idea in mind where they can apply data science techniques and ensure they have access to relevant data.
What this course will cover
This course will provide a flavour of what data science is and includes:
- Basic programming in Python
- Decision science
- Data munging techniques
- Basic machine learning applications
- Version control
- A self-directed project with expert tutors available for guidance
How to join
Long courses
Health Service Modelling Associates Programme (HSMA)
University of Exeter
Delivery: Online
Duration: 15 months (140 hours)
More information
About the course
The Health Service Modelling Associates Programme (HSMA) is designed to foster a culture and skill set in health, social care, and policing organisations, emphasising the routine use of simulation and modelling techniques to aid decision-making processes.
The program is for staff based in health and social care organisations and the police service. Participants are selected based on their current roles, analytical and computer skills, and completion of training modules.
The program includes:
- Over 140 hours of online content
- Up to 15 months of advanced modelling and analysis work within participants’ organisations
The program aims to equip participants with the skills and knowledge to apply advanced modelling techniques in real-world scenarios, fostering a data-driven and informed decision-making culture within participating organisations.
What this course will cover
Phase 1 focuses on Operational Research and Data Science skills, including:
- Programming
- Simulation
- System dynamics
- Geographic modelling
- Artificial intelligence
- Free and open-source software development
In Phase 2, participants undertake their ‘Inception Project’, receiving support from a community of experts. Projects must align with the program’s focus areas and be related to modelling and data science in health, social care, or policing.