LangGraph Training in Belgrade

LangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs that feature persistent state and granular control over execution processes.

This instructor-led live training, available online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions equipped with essential compliance, traceability, and governance controls.

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

• Developing legal-specific LangGraph workflows that ensure auditability and regulatory compliance.
• Incorporating legal ontologies and document standards into graph states and processing mechanisms.
• Establishing guardrails, human-in-the-loop approval processes, and traceable decision pathways.
• Deploying, monitoring, and maintaining LangGraph services in production environments with robust observability and cost management.

Course Format

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

Customization Options

• For customized training requests, please reach out to us to arrange your specific needs.

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

This instructor-led live training, available online or onsite, is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with appropriate governance, observability, and compliance measures.

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

• Creating finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrating financial data standards and ontologies into graph states and tooling.
• Establishing reliability, safety, and human-in-the-loop controls for critical processes.
• Deploying, monitoring, and optimizing LangGraph systems to meet performance, cost, and SLA targets.

Course Format

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

Customization Options

• For customized training requests, please contact us to arrange details.

LangGraph empowers the creation of stateful, multi-actor workflows driven by Large Language Models (LLMs), offering precise control over execution paths and state management. 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, is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based solutions for healthcare while navigating regulatory, ethical, and operational complexities.

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

• Design LangGraph workflows tailored to healthcare needs, prioritizing compliance and auditability.
• Integrate LangGraph applications with established medical ontologies and standards, including FHIR, SNOMED CT, and ICD.
• Apply best practices for reliability, traceability, and explainability within sensitive operational environments.
• Deploy, monitor, and validate LangGraph applications in real-world healthcare production settings.

Course Format

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

Customization Options

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

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

This instructor-led live training, available both online and onsite, targets advanced AI platform engineers, AI DevOps specialists, and ML architects seeking to optimize, debug, monitor, and manage production-grade LangGraph systems.

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

• Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Engineering reliability through the implementation of retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debugging and tracing graph executions, inspecting states, and systematically reproducing production issues.
• Instrumenting graphs with logs, metrics, and traces; deploying to production environments; and monitoring SLAs and costs.

Course Format

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

Customization Options

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

LangGraph is a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving LLMs and tools, making it highly suitable for automating and personalizing content pipelines.

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

Upon completing this training, participants will be able to:

• Design graph-structured content and email workflows incorporating conditional logic.
• Integrate LLMs, APIs, and data sources to enable automated personalization.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimize 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 a customized training session for this course, please contact us to arrange.

LangGraph is a framework designed for composing graph-structured LLM workflows that facilitate branching, tool utilization, memory management, and controllable execution.

This instructor-led, live training (available online or onsite) targets intermediate-level engineers and product teams who aim to combine 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.

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

• Design graph-based workflows that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallbacks for robust execution.
• Integrate retrieval mechanisms, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior for 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 customized training for this course, please contact us to arrange details.

LangGraph is a specialized framework designed for constructing large language model (LLM) applications structured as graphs, enabling capabilities such as planning, branching logic, tool integration, memory management, and controlled execution.

This instructor-led live training session (available online or on-site) is tailored for developers, prompt engineers, and data professionals at the beginner level who aim to design and implement reliable, multi-step LLM workflows utilizing LangGraph.

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

• Articulate core LangGraph concepts, including nodes, edges, and state, and identify appropriate use cases for each.
• Construct prompt chains that support branching, tool invocation, and memory retention.
• 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 combined with guided discussions.
• Hands-on labs and code walkthroughs conducted within a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation methodologies.

Customization Options

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