LangGraph Training in Varna

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

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

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

• Create legal-specific LangGraph workflows that maintain auditability and compliance.
• Incorporate legal ontologies and document standards into graph states and processing.
• Implement guardrails, human-in-the-loop approvals, and traceable decision pathways.
• Deploy, monitor, and maintain LangGraph services in production environments with effective observability and cost management.

Course Format

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

Customization Options

• For tailored training on this subject, please contact us to arrange your specific requirements.

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

This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based finance solutions that adhere to proper governance, observability, and compliance standards.

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 ensure performance, cost efficiency, and SLA compliance.

Course Format

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

Course Customization Options

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

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

This instructor-led live training (available online or onsite) targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.

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

• Design healthcare-specific LangGraph workflows with compliance and auditability as key considerations.
• Integrate LangGraph applications with medical ontologies and standards, including FHIR, SNOMED CT, and ICD.
• Apply best practices for reliability, traceability, and explainability in sensitive environments.
• Deploy, monitor, and validate LangGraph applications within healthcare production settings.

Course Format

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

Course Customization Options

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

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

This instructor-led live training, available online or onsite, targets advanced AI platform engineers, DevOps professionals specializing in AI, 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 improve scalability.
• Ensure reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect state changes, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces; deploy them to production; and monitor SLAs and costs.

Format of the Course

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

Course Customization Options

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

LangGraph is a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving Large Language Models (LLMs) and various tools. It is particularly well-suited for automating and personalizing content pipelines.

This instructor-led live training, available both online and onsite, targets intermediate-level marketers, content strategists, and automation developers looking to build dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Create graph-structured workflows for emails and content that incorporate conditional logic.
• Connect LLMs, APIs, and data sources to enable automated personalization.
• Manage state, memory, and context throughout multi-step campaigns.
• Assess, monitor, and optimize the performance and delivery results of workflows.

Course Format

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

Course Customization Options

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

LangGraph is a framework designed for composing graph-structured workflows involving LLMs, enabling features such as branching, tool usage, memory management, and controllable execution.

This instructor-led, live training (available online or onsite) targets intermediate-level engineers and product teams looking to integrate LangGraph’s graph logic with LLM agent loops to create dynamic, context-aware applications. Examples include customer support agents, decision trees, and information retrieval systems.

Upon completing this training, participants will be capable of:

• Designing graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implementing conditional routing, retries, and fallback mechanisms to ensure robust execution.
• Integrating retrieval mechanisms, APIs, and structured outputs into agent loops.
• Evaluating, monitoring, and hardening agent behavior to enhance reliability and safety.

Course Format

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

Course Customization Options

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

LangGraph is a specialized framework designed for constructing LLM applications with a graph-based architecture. It facilitates advanced capabilities such as planning, branching logic, tool utilization, memory management, and controllable execution flows.

This instructor-led live training, available both online and onsite, is tailored for beginner-level developers, prompt engineers, and data practitioners aiming 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, including nodes, edges, and state, and understand appropriate use cases.
• Construct prompt chains that support branching, tool invocation, and persistent 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 exercises and code walkthroughs within a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation strategies.

Customization Options

• For requests regarding customized training for this course, please contact us to arrange suitable arrangements.