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

Young woman shown from chest up, she is dressed in a white lab coat and blue gloves. She has a stethoscope around her neck and a virtual reality headset over her eyes.

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

Sign up via FutureLearn 

Close up image showing a table with two laptops, a notebook and pens. There are two sets of hands on the table, one is writing in the notebook.

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

Sign up via FutureLearn

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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

Sign up via the University of Bath

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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

Sign up via the University of Bath

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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

Sign up via the University of Bath

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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

Sign up via UWE Bristol

Abstract molecular representation

Molecular Epidemiology

University of Bristol
Start date: 1 May 2024
Duration: 3 days
Delivery: Online
Certification: No CPD award
Cost: £660

More information

About the course

This 3-day 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.

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

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

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.

Close up of rows of test tubes. The end of a pink pipette is entering the top of one of the test tubes.

Designing and Conducting Pragmatic Randomised Controlled Trials

University of Bristol
Start date: 13 May 2024
Duration: 5 days
Delivery: Online
Certification: No CPD award
Cost: £1100

More information

About the course

Pragmatic Randomised Controlled Trial (RCTs) are the ‘gold standard’ test for evaluating whether a new intervention is better than an existing one. They are routinely used in both real-world healthcare and public health settings.

This 5-day course aims to provide an understanding of the essentials of designing, conducting and analysing pragmatic randomised controlled trials (RCTs). The course examines RCTs evaluating health and public health interventions in primary, secondary and community settings with individual and cluster randomised designs.

What this course will cover

  • The need for randomised trials and understanding why and when they are conducted
  • Addressing the key questions in designing a trial
  • Examining issues involved in the planning, conducting and completing a successful trial
  • Protocol adherence and missing data
  • How to assess patient experiences and incorporate patient and public involvement in trials
  • Using strategies to enhance trial recruitment, adherence and retention
  • Understanding the distinctive concepts in the analysis of clinical and health economic data in pragmatic randomised trials
  • An insight into the experience of being a Chief Investigator and working with registered Clinical Trials Units

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.

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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.

Crop of medical doctor holding a clipboard.

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.

Printed yellow biohazard symbol attached to a wall with red tape.

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.

Image of a stethoscope.

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

A man and a woman  shown from above. There is a laptop on a table in front of them and they are holding papers showing graphs and charts.

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

Please complete this expression of interest form

Close up of laptop screen showing computer coding.

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

Please complete this expression of interest form

Long courses

Close up image of lines of computer code.

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.

How to join

See the HSMA website for application information