Building Conversational Agents with LangChain Training Course

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

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

Upon completing this training, participants will be capable of:

• Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Ensuring system reliability through 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 them to production; and monitoring SLAs and costs.

Course Format

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

Customization Options

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

This instructor-led, live training in Sweden (online or onsite) is aimed at developers and IT professionals of all skill levels who wish to automate tasks and processes using AI without writing extensive code.

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

• Design and implement complex workflows using n8n's visual programming interface.
• Integrate AI capabilities into workflows using LangChain.
• Build custom chatbots and virtual assistants for various use cases.
• Perform advanced data analysis and processing with AI agents.

This instructor-led, live training in Sweden (online or onsite) is designed for beginner-level business analysts and automation engineers who wish to understand how to use LangChain and APIs for automating repetitive tasks and workflows.

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

• Grasp the fundamentals of API integration with LangChain.
• Automate repetitive workflows using LangChain and Python.
• Utilize LangChain to connect various APIs for efficient business processes.
• Create and automate custom workflows using APIs and LangChain’s automation capabilities.

This instructor-led, live training in Sweden (online or onsite) is aimed at advanced-level AI researchers and policy makers who wish to explore the ethical implications of AI development and learn how to apply ethical guidelines when building AI solutions with LangChain.

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

• Identify key ethical issues in AI development with LangChain.
• Understand the impact of AI on society and decision-making processes.
• Develop strategies for building fair and transparent AI systems.
• Implement ethical AI guidelines into LangChain-based projects.

This instructor-led, live training in Sweden (online or onsite) is aimed at intermediate-level web developers and UX designers who wish to leverage LangChain to create intuitive and user-friendly web applications.

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

• Grasp the core concepts of LangChain and its role in enhancing web user experience.
• Deploy LangChain within web applications to build dynamic and responsive interfaces.
• Integrate APIs into web apps to boost interactivity and user engagement.
• Refine user experience through LangChain’s advanced customization capabilities.
• Analyze user behavior data to optimize web app performance and overall experience.

This instructor-led, live training in Sweden (online or onsite) is designed for intermediate developers and software engineers who wish to create AI-powered applications using the LangChain framework.

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

• Understand the fundamentals of LangChain and its components.
• Integrate LangChain with large language models (LLMs) like GPT-4.
• Build modular AI applications using LangChain.
• Troubleshoot common issues in LangChain applications.

This instructor-led, live training in Sweden (online or onsite) is tailored for advanced-level data engineers and DevOps professionals who want to utilize LangChain's capabilities through integration with various cloud services.

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

• Integrate LangChain with major cloud platforms such as AWS, Azure, and Google Cloud.
• Utilize cloud-based APIs and services to enhance LangChain-powered applications.
• Scale and deploy conversational agents to the cloud for real-time interaction.
• Implement monitoring and security best practices in cloud environments.

This instructor-led, live training in Sweden (online or on-site) is designed for data professionals with intermediate-level skills who aim to enhance their data analysis and visualization capabilities using LangChain.

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

• Automate data retrieval and cleaning through LangChain.
• Execute advanced data analysis using Python and LangChain.
• Produce visualizations using Matplotlib and other Python libraries integrated with LangChain.
• Use LangChain to generate natural language insights derived from data analysis.

This instructor-led live training in Sweden (online or onsite) is aimed at beginner to intermediate developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain practical skills for building AI-powered applications.

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

• Grasp the fundamental principles of LangChain.
• Set up and configure the LangChain environment.
• Understand the architecture and how LangChain interacts with large language models (LLMs).
• Develop simple applications using LangChain.

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

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

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

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

Course Format

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

Customization Options

• For customized training arrangements, please contact us directly.

LangGraph serves as a framework designed for constructing LLM applications that leverage graph structures, enabling capabilities such as planning, branching, tool utilization, memory management, and controlled execution.

This instructor-led live training, available either online or on-site, targets 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 capable of:

• Explaining fundamental LangGraph concepts (nodes, edges, state) and determining appropriate use cases.
• Developing prompt chains that support branching, tool invocation, and memory retention.
• Integrating retrieval mechanisms and external APIs into graph-based workflows.
• Testing, debugging, and evaluating LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures coupled with facilitated discussions.
• Guided laboratory sessions 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 it.

LangGraph empowers the creation of stateful, multi-actor workflows driven by 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 integrate with medical 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 healthcare solutions while effectively addressing regulatory, ethical, and operational challenges.

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

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

Format of the Course

• Interactive lectures and discussions.
• Hands-on exercises utilizing 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 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) targets intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based legal solutions, ensuring necessary compliance, traceability, and governance controls.

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 with observability and cost controls.

Format of the Course

• Interactive lecture and discussion.
• Numerous exercises and practice opportunities.
• 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 framework designed for constructing graph-structured workflows involving Large Language Models (LLMs). It supports branching logic, tool utilization, memory management, and controllable execution paths.

This instructor-led live training, available both online and onsite, targets intermediate-level engineers and product teams. Participants will learn to combine LangGraph’s graph logic with LLM agent loops to develop dynamic, context-aware applications, including customer support agents, decision trees, and information retrieval systems.

Upon completion 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, external APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior to ensure reliability and safety.

Course Format

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

Course Customization Options

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

LangGraph serves as a graph-based orchestration framework that facilitates conditional, multi-step workflows involving LLMs and tools, making it highly suitable for automating and personalizing content pipelines.

This instructor-led, live training (available 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 completing this training, participants will be capable of:

• Designing graph-structured workflows for content and email that incorporate conditional logic.
• Integrating LLMs, APIs, and data sources to enable 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

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