LangGraph for Marketing Automation 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) is tailored for advanced-level AI platform engineers, AI DevOps professionals, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.

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

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Engineer reliability by implementing retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect state data, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces; deploy to production environments; and monitor SLAs and costs.

Course Format

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

Customization Options

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

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

This instructor-led live training, available online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage finance solutions based on LangGraph, ensuring proper governance, observability, and compliance.

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

• Develop finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph states and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical operations.
• Deploy, monitor, and optimize LangGraph systems to enhance performance, manage costs, and meet SLAs.

Course Format

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

Customization Options

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

LangGraph serves as a framework for constructing LLM applications with graph structures, enabling capabilities such as planning, branching, tool integration, memory management, and controllable execution.

This instructor-led training, available both online and onsite, is tailored for beginner-level developers, prompt engineers, and data professionals looking to design and implement robust, multi-step LLM workflows using LangGraph.

Upon completing this training, participants will be able to:

• Articulate the fundamental concepts of LangGraph (nodes, edges, state) and identify appropriate use cases.
• Construct prompt chains that support branching, tool invocation, and memory retention.
• Incorporate retrieval mechanisms and external APIs into graph-based workflows.
• Conduct testing, debugging, and evaluation of LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures and guided discussions.
• Hands-on labs and code walkthroughs conducted in a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation.

Customization Options

• For personalized training arrangements for this course, please reach out to us.

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 vital for ensuring compliance, enabling interoperability, and developing decision-support systems that align with medical workflows.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced professionals aiming 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 healthcare-specific LangGraph workflows with a focus on compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards (FHIR, SNOMED CT, ICD).
• Apply 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 lecture and discussion.
• Hands-on exercises with real-world case studies.
• Implementation practice in a live-lab environment.

Course Customization Options

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

LangGraph serves as a framework for constructing stateful, multi-actor LLM applications through composable graphs, enabling persistent state management and precise control over execution flow.

This instructor-led live training, available online or on-site, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based legal solutions, ensuring necessary compliance, traceability, and governance controls.

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

• Design LangGraph workflows tailored for legal requirements that maintain auditability and compliance.
• Integrate legal ontologies and document standards into graph states and processing logic.
• Implement guardrails, human-in-the-loop approval mechanisms, and traceable decision paths.
• Deploy, monitor, and maintain LangGraph services in production environments with robust observability and cost management.

Course Format

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

Customization Options

• For customized training arrangements, please reach out to us to coordinate.

LangGraph serves as a framework designed for assembling graph-structured LLM workflows, offering support for branching, tool integration, memory management, and controllable execution.

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

Upon completing this training, participants will be equipped to:

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

Course Format

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

Course Customization Options

• To request customized training for this course, please get in touch with us to make arrangements.