LangGraph in Healthcare: Workflow Orchestration for Regulated Environments Training Course

LangGraph serves as a framework for developing stateful, multi-agent LLM applications by composing graphs with persistent state and execution control.

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

Upon completing this training, participants will be able to:

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Build reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect states, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces; deploy to production; and monitor SLAs and costs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

Agentic AI refers to a methodology where artificial intelligence systems are capable of planning, reasoning, and utilizing tools to achieve specific objectives within established boundaries.

This instructor-led live training, available online or in-person, is designed for intermediate-level healthcare and data professionals seeking to design, assess, and manage agentic AI solutions for both clinical and operational scenarios.

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

• Articulate the core principles and limitations of agentic AI within healthcare environments.
• Construct secure agent workflows that incorporate planning, memory retention, and tool integration.
• Develop retrieval-augmented agents that leverage clinical documentation and knowledge repositories.
• Assess, oversee, and govern agent conduct using safety guardrails and human-in-the-loop mechanisms.

Course Format

• Interactive lectures coupled with guided discussions.
• Directed laboratory exercises and code walkthroughs conducted in a sandbox setting.
• Scenario-based activities focusing on safety, assessment, and governance.

Customization Options

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

This instructor-led, live training in France (online or onsite) is designed for healthcare professionals and AI developers at intermediate to advanced levels 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 guided, live training in France (online or on-site) is designed for intermediate-level healthcare experts looking to utilize AI and AR/VR solutions for medical education, surgical simulations, and rehabilitation processes.

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

• Grasping how AI improves AR/VR experiences within healthcare.
• Utilizing AR/VR for surgical simulations and medical education.
• Implementing AR/VR tools in patient rehabilitation and therapy.
• Examining the ethical and privacy challenges posed by AI-enhanced medical technologies.

This instructor-led, live training conducted in France (either online or on-site) is directed at intermediate-level data scientists and healthcare professionals eager to harness AI for sophisticated healthcare applications using Google Colab.

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

• Implement healthcare-specific AI models using Google Colab.
• Utilize AI for predictive modeling within healthcare data.
• Analyze medical images employing AI-driven techniques.
• Investigate ethical considerations inherent in AI-based healthcare solutions.

This instructor-led, live training in France (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 France (online or onsite) is designed for healthcare professionals and researchers who aim to harness ChatGPT to improve patient care, optimize workflows, and achieve better healthcare outcomes.

Upon completing this training, participants will be equipped to:

• Grasp the fundamental concepts of ChatGPT and its applications in healthcare.
• Employ ChatGPT to automate healthcare processes and manage interactions.
• Deliver precise medical information and support to patients using ChatGPT.
• Apply ChatGPT for medical research and analytical tasks.

This live, instructor-led training held in France (online or onsite) is designed for intermediate-level healthcare professionals, biomedical engineers, and AI developers seeking to harness 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 France (online or onsite) targets intermediate to advanced-level medical AI developers and data scientists who wish to refine 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:

• Refine 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 refined models in real-world healthcare environments.

Generative AI is a technology that creates new content such as text, images, and recommendations based on prompts and data.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level healthcare professionals who wish to use generative AI and prompt engineering to improve efficiency, accuracy, and communication in medical contexts.

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

• Grasp the core concepts of generative AI and prompt engineering.
• Leverage AI tools to streamline clinical, administrative, and research workflows.
• Ensure ethical, safe, and compliant use of AI in healthcare.
• Refine prompts to achieve consistent and accurate results.

Format of the Course also allows for the evaluation of participants.

• Interactive lecture and discussion.
• Practical exercises and case studies.
• Hands-on experimentation with AI tools.

Course Customization Options

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

LangGraph serves as a framework designed for constructing stateful, multi-agent Large Language Model (LLM) applications through composable graphs, featuring persistent state and precise execution control.

This instructor-led, live training—available either online or onsite—is tailored for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions that adhere to strict governance, observability, and compliance standards.

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

• Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph states and associated tooling.
• Implement reliability, safety, and human-in-the-loop controls essential for critical processes.
• Deploy, monitor, and optimize LangGraph systems to ensure optimal performance, cost-efficiency, and adherence to Service Level Agreements (SLAs).

Course Format

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

Customization Options

• To request customized training for this course, please contact us to arrange your specific needs.

LangGraph is a framework designed for constructing graph-structured Large Language Model (LLM) applications, supporting capabilities such as planning, branching, tool usage, memory management, and controllable execution.

This instructor-led, live training (available online or onsite) is designed for beginner-level developers, prompt engineers, and data practitioners who aim to design and build reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and determine when to apply them.
• Construct prompt chains that branch, invoke tools, and maintain memory.
• Integrate retrieval mechanisms and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph applications for reliability and safety.

Course Format

• Interactive lectures and facilitated discussions.
• Guided labs and code walkthroughs within a sandbox environment.
• Scenario-based exercises focused on design, testing, and evaluation.

Course Customization Options

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

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

This instructor-led live training, available both online and onsite, targets intermediate to advanced professionals who aim to design, implement, and manage LangGraph-based legal solutions, ensuring the necessary compliance, traceability, and governance controls are in place.

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

• Design legal-specific LangGraph workflows that maintain 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 environments with observability and cost controls.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation within a live laboratory 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 powered by Large Language Models (LLMs). It supports features such as branching logic, tool integration, memory management, and controllable execution.

This instructor-led, live training session (available online or onsite) is tailored for intermediate-level engineers and product teams. Participants will learn to combine LangGraph's graph-based logic with LLM agent loops to construct dynamic, context-aware applications, including customer support agents, decision trees, and information retrieval systems.

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

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

Course Format

• Interactive lectures and facilitated discussions.
• Guided laboratory exercises and code walkthroughs within a sandbox environment.
• Scenario-based design tasks and peer review sessions.

Customization Options

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

LangGraph serves as a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving LLMs and tools, making it an excellent choice for automating and personalizing content pipelines.

This instructor-led live training, available either online or on-site, targets intermediate-level marketers, content strategists, and automation developers who aim to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Designing graph-structured content and email workflows that incorporate conditional logic.
• Integrating LLMs, APIs, and data sources to achieve automated personalization.
• Managing state, memory, and context throughout multi-step campaigns.
• Evaluating, monitoring, and optimizing workflow performance and delivery outcomes.

Course Format

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

Course Customization Options

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