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
Healthcare analytics with Excel: spreadsheet modelling and optimisation
Cardiff University
Start date: 2 September 2024
Duration: 8 hours independent learning and 1-hour live online session
Delivery: Online (delivered via Learning Central)
Certification: CPD Certified
Cost: £500 (if you work for a Health board, you are eligible for a free/discounted place)
More information
About the course
Data analysis is crucial for making informed decisions and improving patient outcomes. Microsoft Excel is as a powerful platform for healthcare professionals to organise, analyse, and interpret data.
This course aims to unlock the analytical potential of Excel through an exploration of its formulas, functions and solver package for mathematical modelling. It will equip learners with the knowledge and tools to leverage Excel for data-driven decision-making in healthcare.
It is designed for healthcare managers, administrators, and clinicians who are seeking to enhance their data analysis skills using Microsoft Excel. It caters to individuals who work in various healthcare settings.
What this course will cover
- Fundamental Excel formulas and functions
- Statistical analysis in healthcare management
- Advanced data manipulation and visualisation
- Pivot tables and pivot charts
- Optimisation using Excel
- Practical applications and case studies in healthcare
Further details and how to join
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
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
Machine Learning - Coming soon
University of Bath
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
Coming soon
Business Analytics in Practice - Coming soon
University of Bath
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
Coming soon
Foundations Of Health and Wellbeing - Coming soon
University of Bristol
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 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
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
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. The programe is supported by the NHS Digital Academy.
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.