LangGraph in Healthcare: Workflow Orchestration for Regulated Environments Training Course

LangGraph is a framework designed for constructing stateful, multi-actor LLM applications as composable graphs, featuring persistent state and precise control over execution.

This instructor-led, live training (available online or onsite) targets advanced-level AI platform engineers, AI DevOps specialists, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.

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

• Design and optimize complex LangGraph topologies for speed, cost efficiency, and scalability.
• Enhance reliability through retries, timeouts, idempotency, and checkpoint-based recovery.
• Debug and trace graph executions, inspect state, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces, deploy to production, and monitor SLAs and costs.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

Agentic AI represents a paradigm where artificial intelligence systems autonomously plan, reason, and utilize tools to achieve specific objectives within established boundaries.

This instructor-led training, available online or onsite, is designed for intermediate-level healthcare and data teams looking to design, evaluate, and govern agentic AI solutions for both clinical and operational scenarios.

Upon completion of this course, participants will be capable of:

• Articulating the core concepts and constraints of agentic AI within healthcare environments.
• Constructing secure agent workflows that incorporate planning, memory mechanisms, and tool integration.
• Developing retrieval-augmented agents tailored to clinical documents and knowledge bases.
• Implementing evaluation, monitoring, and governance frameworks for agent behavior using guardrails and human-in-the-loop controls.

Course Format

• Interactive lectures combined with facilitated group discussions.
• Guided laboratory exercises and code walkthroughs within a sandbox environment.
• Scenario-based practical exercises focusing on safety, evaluation, and governance.

Customization Options

• To request tailored training for this course, please reach out to us to arrange.

This instructor-led, live training in Czech Republic (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.

Designed for intermediate-level healthcare professionals interested in leveraging AI and AR/VR for medical education, surgical simulations, and rehabilitation, this instructor-led live training is available either online or on-site in Czech Republic.

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

• Comprehend how AI enhances AR/VR experiences within healthcare.
• Utilize AR/VR for surgical simulations and medical education.
• Implement AR/VR tools for patient rehabilitation and therapeutic treatments.
• Examine the ethical and privacy challenges associated with AI-enhanced medical technologies.

This instructor-led live training, available online or on-site, is designed for intermediate-level data scientists and healthcare professionals seeking to harness AI for advanced healthcare applications using Google Colab.

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

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

This instructor-led, live training, available online or on-site, is designed for intermediate-level healthcare professionals and data scientists aiming to understand and apply AI technologies in healthcare environments.

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

• Recognize significant healthcare challenges that AI solutions can resolve.
• Evaluate the impact of AI on patient care, safety, and medical research.
• Comprehend the intersection of AI and healthcare business models.
• Apply core AI principles to real-world healthcare scenarios.
• Construct machine learning models for the analysis of medical data.

This instructor-led, live training in Czech Republic (online or onsite) is designed for healthcare professionals and researchers who aim to utilize ChatGPT to enhance patient care, optimize workflows, and improve healthcare outcomes.

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

• Comprehend the fundamentals of ChatGPT and its applications in healthcare.
• Leverage 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 Czech Republic (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 Czech Republic (online or onsite) targets intermediate to advanced medical AI developers and data scientists who aim to fine-tune models for clinical diagnosis, disease prediction, and patient outcome forecasting using 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 in medical contexts.
• Address privacy concerns, bias mitigation, and regulatory compliance during model development.
• Deploy and monitor fine-tuned models in real-world healthcare environments.

Generative AI refers to technologies capable of producing new content, including text, images, and tailored recommendations, derived from specific prompts and underlying data.

This instructor-led training session, available either online or on-site, is designed for healthcare professionals at beginner to intermediate levels. The course aims to equip participants with the skills to leverage generative AI and prompt engineering to enhance efficiency, accuracy, and communication within medical environments.

Upon completing this training, participants will be able to:

• Grasp the core concepts of generative AI and prompt engineering.
• Utilize AI tools to streamline clinical, administrative, and research workflows.
• Ensure the ethical, secure, and compliant application of AI in healthcare settings.
• Refine prompts to achieve reliable and precise outcomes.

Course Format

• Interactive lectures accompanied by discussion.
• Practical exercises and real-world case studies.
• Hands-on experimentation with AI tools.

Customization Options

• To request a customized version of this course, please contact us to arrange your needs.

LangGraph serves as a framework designed for constructing stateful, multi-agent LLM applications through composable graphs that maintain persistent state and precise execution control.

This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals looking to design, implement, and operate LangGraph-based financial solutions that ensure proper governance, observability, and compliance.

Upon completion of this training, participants will be capable of:

• Designing finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrating financial data standards and ontologies into graph states and tooling.
• Implementing reliability, safety, and human-in-the-loop controls for critical processes.
• Deploying, monitoring, and optimizing LangGraph systems to achieve desired performance, cost efficiency, and SLAs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live laboratory environment.

Customization Options

• To request tailored training for this course, please contact us to arrange it.

LangGraph serves as a framework for constructing graph-structured LLM applications that facilitate planning, branching, tool utilization, memory management, and controllable execution.

This instructor-led live training, available both online and on-site, targets beginner-level developers, prompt engineers, and data practitioners who aim to design and implement reliable, multi-step LLM workflows using LangGraph.

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

• Articulate core LangGraph concepts (nodes, edges, state) and understand their appropriate use cases.
• Construct prompt chains capable of branching, invoking tools, and maintaining memory.
• Integrate retrieval mechanisms and external APIs into graph-based workflows.
• Test, debug, and evaluate LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures coupled with facilitated discussions.
• Guided laboratory sessions and code walkthroughs within a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation.

Customization Options

• To request customized training for this course, please contact us to make arrangements.

LangGraph serves as a framework for constructing stateful, multi-agent LLM applications through composable graphs that maintain persistent state and offer precise execution control.

This instructor-led live training (available online or onsite) is designed for intermediate to advanced professionals aiming to design, implement, and operate LangGraph-based legal solutions with essential compliance, traceability, and governance controls.

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

• Design legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrate legal ontologies and document standards into graph state and processing.
• Implement guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploy, monitor, and maintain LangGraph services in production with observability and cost controls.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practical application.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

LangGraph is a framework designed for composing graph-structured workflows involving Large Language Models (LLMs) that facilitate branching, tool utilization, memory management, and controlled execution.

This instructor-led live training, available online or onsite, targets intermediate-level engineers and product teams looking to merge LangGraph’s graph logic with LLM agent loops. The goal is to develop dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

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

• Design graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallback mechanisms to ensure robust execution.
• Integrate retrieval processes, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and enhance agent behavior to ensure reliability and safety.

Course Format

• Interactive lectures and facilitated discussions.
• Guided labs and code walkthroughs conducted in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Customization Options

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

LangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured content and email workflows with conditional logic.
• Integrate LLMs, APIs, and data sources for automated personalization.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimize workflow performance and delivery outcomes.

Format of the Course

• Interactive lectures and group discussions.
• Hands-on labs implementing email workflows and content pipelines.
• Scenario-based exercises on personalization, segmentation, and branching logic.

Course Customization Options

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