LangGraph Training in Nantes

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 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 facilitates stateful, multi-actor workflows driven by Large Language Models (LLMs), offering precise control over execution paths and state persistence. These capabilities are essential in healthcare for ensuring compliance, enabling interoperability, and developing decision-support systems that align with clinical workflows.

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

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

• Design LangGraph workflows tailored to healthcare, ensuring compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
• Apply best practices for reliability, traceability, and explainability in sensitive environments.
• Deploy, monitor, and validate LangGraph applications in healthcare production settings.

Course Format

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

Customization Options

• To request a customized version of this training, please contact us to arrange.

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.

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.

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 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.