Generative AI and Prompt Engineering in Healthcare Training Course

This instructor-led training in Greece delves into advanced fine-tuning and prompt management within Vertex AI, assisting intermediate and advanced practitioners in optimizing Gemini models, implementing stringent evaluation workflows, and deploying dependable generative AI solutions for real-world enterprise scenarios.

Delve into the world of agentic AI in healthcare through this instructor-led training in Greece. Develop the skills to design, assess, and govern agent workflows tailored for clinical applications. Participants will construct retrieval-augmented agents, implement safety guardrails, and master governance frameworks via practical labs and scenario-based training.

This instructor-led, live training in Greece (online or onsite) is designed for intermediate to advanced-level healthcare professionals and AI developers aiming to implement AI-driven healthcare solutions.

Upon completion of this training, participants will be able to:

• Grasp the role of AI agents in healthcare and diagnostics.
• Build AI models for medical image analysis and predictive diagnostics.
• Integrate AI with electronic health records (EHR) and clinical workflows.
• Ensure compliance with healthcare regulations and adhere to ethical AI practices.

This instructor-led, live training in Greece (online or onsite) is aimed at intermediate-level healthcare professionals who wish to apply AI and AR/VR solutions for medical training, surgery simulations, and rehabilitation.

By the end of this training, participants will be able to:

• Understand the role of AI in enhancing AR/VR experiences in healthcare.
• Use AR/VR for surgery simulations and medical training.
• Apply AR/VR tools in patient rehabilitation and therapy.
• Explore the ethical and privacy concerns in AI-enhanced medical tools.

This instructor-led live training in Greece (online or onsite) is aimed at intermediate-level data scientists and healthcare professionals who wish to leverage AI for advanced healthcare applications using Google Colab.

By the end of this training, participants will be able to:

• Implement AI models for healthcare using Google Colab.
• Use AI for predictive modeling in healthcare data.
• Analyze medical images with AI-driven techniques.
• Explore ethical considerations in AI-based healthcare solutions.

This instructor-led, live training in Greece (online or onsite) is aimed at intermediate-level healthcare professionals and data scientists who wish to understand and apply AI technologies in healthcare environments.

By the end of this training, participants will be able to:

• Identify key healthcare challenges that AI can address.
• Analyze AI’s impact on patient care, safety, and medical research.
• Understand the relationship between AI and healthcare business models.
• Apply fundamental AI concepts to healthcare scenarios.
• Develop machine learning models for medical data analysis.

This instructor-led, live training in Greece (online or onsite) is designed for healthcare professionals and researchers who wish to leverage ChatGPT to enhance patient care, streamline workflows, and improve healthcare outcomes.

By the end of this training, participants will be able to:

• Understand the fundamentals of ChatGPT and its applications in healthcare.
• Utilize ChatGPT to automate healthcare processes and interactions.
• Provide accurate medical information and support to patients using ChatGPT.
• Apply ChatGPT for medical research and analysis.

This instructor-led, live training Greece (online or onsite) is designed for intermediate-level healthcare professionals, biomedical engineers, and AI developers aiming to leverage Edge AI for innovative healthcare solutions.

By the end of this training, participants will be able to:

• Understand the role and advantages of Edge AI in healthcare.
• Develop and deploy AI models on edge devices for healthcare applications.
• Implement Edge AI solutions in wearable devices and diagnostic tools.
• Design and deploy patient monitoring systems using Edge AI.
• Address ethical and regulatory considerations in healthcare AI applications.

This instructor-led, live training in Greece (online or onsite) is designed for intermediate to advanced medical AI developers and data scientists looking to fine-tune models for clinical diagnosis, disease prediction, and patient outcome forecasting using both structured and unstructured medical data.

Upon completion of this training, participants will be able to:

• Fine-tune AI models on healthcare datasets, including EMRs, imaging, and time-series data.
• Apply transfer learning, domain adaptation, and model compression techniques within medical contexts.
• Address privacy concerns, bias, and regulatory compliance during model development.
• Deploy and monitor fine-tuned models in real-world healthcare environments.

This instructor-led, live training in Greece (online or onsite) is designed for healthcare professionals, data analysts, and policymakers at beginner to intermediate levels who wish to understand and apply generative AI in the context of healthcare.

By the end of this training, participants will be able to:

• Explain the principles and applications of generative AI in healthcare.
• Identify opportunities for generative AI to enhance drug discovery and personalized medicine.
• Utilize generative AI techniques for medical imaging and diagnostics.
• Assess the ethical implications of AI in medical settings.
• Develop strategies for integrating AI technologies into healthcare systems.

Dive into LangGraph for healthcare through this live training in Greece, designed for intermediate to advanced professionals. Discover how to craft stateful, compliant workflows, integrate key standards like FHIR and SNOMED CT, and tackle ethical and operational challenges within regulated environments.

This instructor-led live training in Greece (online or onsite) targets intermediate to advanced healthcare professionals, medical researchers, and AI developers wishing to apply multimodal AI in medical diagnostics and healthcare applications.

Upon completion of this training, participants will be able to:

• Grasp the role of multimodal AI in contemporary healthcare.
• Combine structured and unstructured medical data for AI-driven diagnostics.
• Utilize AI techniques to analyse medical images and electronic health records.
• Create predictive models for disease diagnosis and treatment recommendations.
• Implement speech recognition and natural language processing (NLP) for medical transcription and patient engagement.

This live training session on Greece supports healthcare practitioners and IT teams in implementing Ollama for local LLMs. Discover how to integrate AI into clinical workflows, tailor models for specific duties, and maintain rigorous data privacy and regulatory compliance within secure healthcare settings.

This instructor-led live training in Greece (online or onsite) targets intermediate-level healthcare professionals and AI developers who wish to apply prompt engineering techniques to enhance medical workflows, research efficiency, and patient outcomes.

By the end of this training, participants will be able to:

• Understand the fundamentals of prompt engineering in healthcare.
• Use AI prompts for clinical documentation and patient interactions.
• Leverage AI for medical research and literature review.
• Enhance drug discovery and clinical decision-making with AI-driven prompts.
• Ensure compliance with regulatory and ethical standards in healthcare AI.

This instructor-led live training on Greece focuses on implementing TinyML solutions for healthcare monitoring and diagnostics. Participants will learn to design models for real-time health data processing, optimize for low-power wearables, and ensure clinical reliability. The course includes hands-on lab exercises.