About
Get ready to dive into real-world healthcare problems using machine learning. This interactive, in-person workshop gives you hands-on experience with real clinical data and tools , no advanced programming background required, only curiosity.
You will build and train your own ML model, create a user interface to expose it, and explore how AI is transforming clinical practice , from diagnosis support to patient outcome prediction.
Understand how ML tools are built and how to critically evaluate AI-assisted clinical decision support.
Gain practical skills to apply ML methods to healthcare datasets in your own research projects.
Build foundational ML skills with a healthcare focus — ideal for health informatics and biomedical programmes.
Extend your engineering skills into the healthcare domain and learn deployment patterns for clinical ML applications.
Learning Outcomes
By the end of the workshop you will have built a working ML model and developed practical skills you can apply immediately.
Grasp the fundamentals of supervised learning, model training, validation, and evaluation in a healthcare context.
Apply data preprocessing, feature engineering, and exploratory analysis techniques to real-world health datasets.
Implement a complete machine learning pipeline — from raw data to a trained, validated predictive model.
Wrap your model in a user-facing interface so it can be demonstrated and interacted with by end users.
Interpret accuracy, precision, recall, ROC curves, and understand the clinical implications of model errors.
Recognise bias, fairness, and accountability challenges when deploying ML in clinical environments.
Programme
A structured full-day programme balancing theory with extensive hands-on coding sessions.
Registration, networking, and informal introductions in the Sophia Suite.
Overview of ML concepts, the healthcare data landscape, and real-world clinical applications. No prior experience required.
Coffee & refreshments — Sophia Suite.
Work with a real clinical dataset. Data cleaning, handling missing values, feature engineering, and visualisation using Python and Jupyter notebooks.
Lunch provided. Opportunity for networking and Q&A with organisers.
Implement a supervised learning pipeline. Train classification models, tune hyperparameters, and validate performance on held-out clinical data.
Coffee & refreshments.
Deploy your trained model by wrapping it in an interactive user interface. See your ML model in action as a clinical decision support tool.
Review key takeaways, open Q&A, resources for continuing your ML journey in healthcare.
Organisers
Researcher and educator specialising in applied machine learning and health informatics. Passionate about making AI accessible to healthcare professionals.
Expert in data science and predictive modelling with extensive experience applying ML techniques to clinical and biomedical research problems.
Venue
6 August 2026
Kingsway, Greyfriars Road
Cardiff CF10 3HH, UK
Thursday, 6 August 2026
8:00 AM – 4:00 PM (BST)
Sophia Suite
5 min walk from Cardiff Central station.
14 October 2026
Kalastajatorpantie 1
00330 Helsinki, Finland
Wednesday, 14 October 2026
8:00 AM – 4:00 PM (EEST)
Coming soon — check back for the Eventbrite link.
Located on the Munkkiniemi peninsula, 7 km from Helsinki city centre.
Registration
Ready to dive into machine learning with a focus on healthcare? Join us for a super interactive, in-person workshop where you will get your hands dirty with real-world data and tools. Whether you are new or have some experience, this session will boost your skills and show you how AI is changing the healthcare game.
This workshop is designed for beginners in machine learning. No advanced programming or data science background is required — only curiosity and a willingness to explore how AI is transforming healthcare. You will develop and train your own ML model and create a user interface to expose it.
Please bring your own device. Participants must bring a laptop to the workshop. Shared or loaned devices are not available on the day. Ensure your laptop has at least 8 GB RAM and that you have permission to install software.
Both events run the same full-day programme. Choose the location that works best for you — spaces are limited.
6 August 2026
14 October 2026
Join clinicians, researchers, students, and developers for a full day of hands-on machine learning. Spaces are limited — secure your place early.