Generative AI and Prompt Engineering in Healthcare Training Course

Delve into agentic AI for healthcare through this instructor-led training in Uzbekistan. Learn to architect, evaluate, and manage agent workflows designed for clinical applications. Participants will construct retrieval-augmented agents, implement guardrails, and gain mastery over governance through practical labs and scenario-based challenges.

This instructor-led, live training in Uzbekistan (online or onsite) is tailored for intermediate to advanced healthcare professionals and AI developers seeking to deploy AI-driven healthcare solutions.

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

• Understand the role of AI agents in healthcare and diagnostics.
• Develop 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 ethical AI practices.

This instructor-led, live training in Uzbekistan (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 Uzbekistan (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 Uzbekistan (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 Uzbekistan (available online or on-site) 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 in Uzbekistan (available online or on-site) is designed for intermediate-level healthcare professionals, biomedical engineers, and AI developers who wish to leverage Edge AI to create innovative healthcare solutions.

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

• Understand the role and benefits 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 guided, live training in Uzbekistan (online or onsite) is designed for intermediate to advanced medical AI developers and data scientists aiming to optimize models for clinical diagnosis, disease prediction, and patient outcome forecasting using structured and unstructured medical data.

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

• Optimize AI models on healthcare datasets, including EMRs, imaging, and time-series data.
• Utilize transfer learning, domain adaptation, and model compression in medical scenarios.
• Handle privacy, bias, and regulatory compliance aspects in model development.
• Deploy and monitor optimized models in real-world healthcare environments.

This instructor-led, live training in Uzbekistan (online or on-site) is aimed at beginner-level to intermediate-level healthcare professionals, data analysts, and policy makers 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 personalised medicine.
• Utilise 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 Uzbekistan, specifically crafted for intermediate to advanced professionals. Acquire the skills to design stateful, compliant workflows, integrate standards like FHIR and SNOMED CT, and navigate the ethical and operational challenges inherent in regulated environments.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level to advanced-level healthcare professionals, medical researchers, and AI developers who wish to apply multimodal AI in medical diagnostics and healthcare applications.

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

• Understand the role of multimodal AI in modern healthcare.
• Integrate structured and unstructured medical data for AI-driven diagnostics.
• Apply AI techniques to analyse medical images and electronic health records.
• Develop predictive models for disease diagnosis and treatment recommendations.
• Implement speech and natural language processing (NLP) for medical transcription and patient interaction.

This live training in Uzbekistan empowers healthcare practitioners and IT teams to deploy Ollama for local LLM utilization. Participants will learn to integrate AI into clinical workflows, customize models for specific tasks, and uphold strict data privacy and regulatory compliance standards within secure healthcare settings.

This instructor-led, live training in Uzbekistan (online or on-site) is designed for intermediate-level healthcare professionals and AI developers who wish to apply prompt engineering techniques to improve 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 reviews.
• Enhance drug discovery and clinical decision-making with AI-driven prompts.
• Ensure compliance with regulatory and ethical standards in healthcare AI.

This live, instructor-led training in Uzbekistan delves into the essential principles and practical aspects of AI in telemedicine. It enables participants to develop practical skills with ChatGPT, Claude, and enterprise automation, directly applicable to real-world clinical settings and contemporary healthcare requirements.

This live, instructor-led training in Uzbekistan focuses on implementing TinyML solutions for healthcare monitoring and diagnostics. Participants will master the design of models for real-time health data, learn to optimize them for low-power wearables, and ensure clinical reliability. The course includes practical, hands-on lab exercises to reinforce learning.