This is a training designed to equip healthcare professionals with skills to integrate advanced AI tools into their daily work

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) : 4 December, 11:00–12:00

Workshop Session (6 hours in person) : 11 December, 13:00–18:00

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 la

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