Prompt Engineering for Healthcare Training Course

Agentic AI is an approach where artificial intelligence systems are designed to plan, reason, and take tool-using actions to achieve specific goals within predefined constraints.

This instructor-led, live training (available both online and on-site) is tailored for intermediate-level healthcare and data teams who aim to design, evaluate, and govern agentic AI solutions for clinical and operational applications.

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

• Understand and explain the principles and limitations of agentic AI in healthcare settings.
• Develop safe workflows for agents that include planning, memory, and tool usage capabilities.
• Create retrieval-augmented agents to access clinical documents and knowledge bases effectively.
• Assess, monitor, and manage agent behavior using guardrails and human-in-the-loop controls.

Format of the Course

• Interactive lectures and facilitated discussions.
• Guided labs and code walkthroughs in a secure sandbox environment.
• Scenario-based exercises focused on safety, evaluation, and governance.

Course Customization Options

• For customized training sessions tailored to your specific needs, please contact us to arrange.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level to advanced-level healthcare professionals and AI developers who wish to implement AI-driven healthcare solutions.

By the end 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 (online or onsite) is aimed at 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 (online or onsite) is aimed at intermediate-level healthcare professionals, biomedical engineers, and AI developers who wish to leverage Edge AI for 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 instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level to advanced-level medical AI developers and data scientists who wish to fine-tune models for clinical diagnosis, disease prediction, and patient outcome forecasting using structured and unstructured medical data.

By the end 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 in medical contexts.
• Address privacy, bias, and regulatory compliance in model development.
• Deploy and monitor fine-tuned models in real-world healthcare environments.

Generative AI is a technology that generates new content, including text, images, and recommendations, based on prompts and data.

This instructor-led, live training (available online or onsite) is designed for healthcare professionals at beginner to intermediate levels who want to leverage generative AI and prompt engineering to enhance efficiency, accuracy, and communication in medical settings.

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

• Grasp the core principles of generative AI and prompt engineering.
• Utilize AI tools to streamline clinical, administrative, and research tasks.
• Ensure ethical, safe, and compliant use of AI in healthcare settings.
• Optimize prompts to achieve consistent and accurate outcomes.

Format of the Course

• Interactive lectures and discussions.
• Practical exercises and case studies.
• Hands-on experimentation with AI tools.

Course Customization Options

• For a customized training session tailored to your specific needs, please contact us to arrange.

This instructor-led, live training in Uzbekistan (online or onsite) 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 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.

LangGraph facilitates stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these features are essential for compliance, interoperability, and developing decision-support systems that align with medical processes.

This instructor-led, live training (conducted online or on-site) is designed for intermediate to advanced professionals who aim to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.

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

• Create healthcare-specific LangGraph workflows with a focus on compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
• Implement best practices for reliability, traceability, and explainability in sensitive environments.
• Deploy, monitor, and validate LangGraph applications in healthcare production settings.

Format of the Course

• Interactive lectures and discussions.
• Practical exercises with real-world case studies.
• Hands-on implementation practice in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

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 analyze 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.

Ollama is a lightweight platform designed for running large language models locally.

This instructor-led, live training (available online or on-site) is tailored for intermediate-level healthcare professionals and IT teams who aim to deploy, customize, and operationalize AI solutions based on Ollama within clinical and administrative settings.

After completing this training, participants will be able to:

• Install and configure Ollama for secure use in healthcare environments.
• Integrate local large language models into clinical workflows and administrative processes.
• Customize models to suit healthcare-specific terminology and tasks.
• Implement best practices for privacy, security, and regulatory compliance.

Format of the Course

• Interactive lectures and discussions.
• Hands-on demonstrations and guided exercises.
• Practical implementation in a simulated healthcare environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at AI practitioners and enthusiasts who wish to harness the power of prompts to generate impressive and realistic text and images.

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

• Have a solid understanding of prompt engineering concepts.
• Write accurate and effective prompts for ChatGPT, Stable Diffusion, DALL-E 2, Leonardo AI, and MidJourney.
• Generate hyper-realistic text and images using the latest tools and techniques in prompt engineering.
• Use AI-powered prompt engineering tools to automate prompt generation.
• Apply prompt engineering to various use cases.
• Incorporate prompt engineering into their own projects and workflows.

TinyML involves integrating machine learning into low-power, resource-limited wearable and medical devices.

This instructor-led, live training (available online or on-site) is designed for intermediate-level practitioners who want to implement TinyML solutions for healthcare monitoring and diagnostic applications.

After completing this training, participants will be able to:

• Design and deploy TinyML models for real-time health data processing.
• Collect, preprocess, and interpret biosensor data to gain AI-driven insights.
• Optimize models for low-power and memory-constrained wearable devices.
• Assess the clinical relevance, reliability, and safety of TinyML-generated outputs.

Format of the Course

• Lectures enhanced by live demonstrations and interactive discussions.
• Hands-on practice with data from wearable devices and TinyML frameworks.
• Implementation exercises in a guided laboratory environment.

Course Customization Options

• For customized training that aligns with specific healthcare devices or regulatory processes, please contact us to tailor the program.