About this Event
Overview of CPD
Join us for an advanced training program designed for healthcare professionals who want to move beyond introductory generative AI use and begin building practical, secure, and reusable AI-powered workflows in their own professional settings. This CPD course focuses on applied automation using n8n together with local language models installed directly on participants’ computers, enabling learners to experiment with powerful AI workflows while gaining a stronger understanding of privacy-conscious and locally controlled deployment options.
This CPD program offers a blended learning approach, combining in-person instruction with guided hands-on practice to provide practical strategies for automating repetitive tasks, improving information access, supporting research workflows, and building useful internal AI assistants. Participants will work through a series of real-world healthcare-oriented case studies that demonstrate how AI can be embedded into routine professional processes in a structured and responsible way.
This CPD is tailored for clinicians, researchers, and healthcare managers seeking to move from general AI familiarity to practical implementation. Key learning outcomes include:
- Installing and running a local language model on a personal computer for practical experimentation.
- Building and adapting n8n workflows for healthcare and research use cases.
- Applying AI automation patterns to triage, retrieval over internal knowledge, and evidence ingestion.
- Ensuring responsible use through appropriate governance, privacy awareness, and human oversight.
By the end of this program, participants will have the practical skills and confidence to prototype and adapt AI-assisted workflows for real professional settings, while understanding the operational and governance considerations required for responsible adoption in healthcare.
Course Details
This program takes a flexible, blended approach, combining in-person instruction with self-paced online learning. Participants will have access to online resources, allowing them to explore the material at their own rhythm.
Participants will join a one-hour online starter session to set expectations and background knowledge. An in-person workshop will offer hands-on experience with AI tools, focusing on real-world applications specifically for people working in healthcare.
To accommodate busy schedules, the workshop is offered several times a year on Friday afternoons. This structure ensures professionals can deepen their understanding of generative AI without disrupting their work commitments
Starter Session (1 hour online) : June 5, 2026
Workshop Session (6 hours in person) : June 12, 2026
Platform: Blackboard, Chat GPT Plus, Zoom
Course Learning Outcomes:
Participants of this course will:
- understand the main components of a practical AI workflow and how they can be applied in professional settings
- install and use a local language model for hands-on experimentation and testing
- build and adapt simple AI-assisted automations to support routine work
- use generative AI to classify, organise, and route information more efficiently
- recognise key considerations relating to quality, privacy, governance, and human oversight when using AI in practice
Bio
Dr. Guido Giunti is the Chief Data Officer at St. James’s Hospital, Dublin, leading efforts to foster a data-driven culture with a human touch. He holds academic positions as an Adjunct Professor at Trinity College Dublin, the University of Oulu and University of Buenos Aires, contributing to medical education, digital health research, and the integration of emerging technologies into clinical practice.
With a background in clinical medicine, digital health, and human-computer interaction, Guido has worked across academic, clinical, and industry settings in Europe. Recognized internationally for his contributions, he has received awards such as the JCI Ten Outstanding Young Persons Award and HIMSS Changemaker in Health. He has led multiple initiatives blending healthcare, technology, and entrepreneurship to drive meaningful change in the digital health landscape.
Jack Doherty is a data science professional with a strong interdisciplinary background spanning mathematics, music, and biomedical research. He completed a B.A. (Moderatorship) in Mathematics and Music with First Class Honours at Trinity College Dublin. He later completed a Postgraduate Diploma in Data Science with Distinction at Technological University Dublin, developing expertise in statistical analysis, machine learning, and data visualization using tools such as Python and SQL.
Jack has developed substantial experience working with clinical and biomedical data through research roles associated with St. James’s Hospital and Trinity College Dublin. As a research assistant he has organised and analysed large clinical datasets, including compiling information from more than 600 emergency department seizure presentations. Over the past year he has further expanded his research profile by working as a data scientist with FutureNeuro, applying data science methods to neurological research and helping to extract meaningful insights from complex biomedical datasets.
Find out more by emailing:
Dr. Guido Giunti at [email protected] for academic queries
Archita Choudhury at [email protected] for administrative queries
Acknowledgement of EU support
Development of this stand-alone module was co-funded by the European Union Digital Europe Programme “Sustainable Healthcare with Digital Health Data Competence” Grant Agreement No. 101190010.
Event Venue & Nearby Stays
Trinity Centre for Health Sciences, 8 James's Street, Dublin 8, Ireland
EUR 500.00 to EUR 780.00
