LangChain for Data Analysis and Visualization Training Course

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

This instructor-led live training, available online or onsite, targets advanced AI platform engineers, AI DevOps specialists, and ML architects looking to optimize, debug, monitor, and operate 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 into systems using retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect states, and systematically reproduce issues encountered in production.
• Instrument graphs with logs, metrics, and traces, deploy them to production, and monitor SLAs and associated costs.

Course Format

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

Customization Options

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

This instructor-led live training in Norway (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 Norway (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.

Upon completing this training, participants will be able to:

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

This instructor-led, live training in Norway (online or onsite) targets intermediate-level professionals eager to deepen their understanding of conversational agents and apply LangChain to real-world use cases.

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

• Grasp the core principles of LangChain and its role in building conversational agents.
• Create and deploy conversational agents utilizing LangChain.
• Integrate conversational agents with APIs and external services.
• Apply Natural Language Processing (NLP) techniques to enhance the performance of conversational agents.

This instructor-led, live training in Norway (online or onsite) is designed for advanced-level AI researchers and policy makers who want to delve into the ethical implications of AI development and learn how to apply ethical guidelines when constructing 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 Norway (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:

• Understand the fundamental concepts of LangChain and its role in enhancing web user experience.
• Implement LangChain in web apps to create dynamic and responsive interfaces.
• Integrate APIs into web apps to improve interactivity and user engagement.
• Optimize user experience using LangChain’s advanced customization features.
• Analyze user behavior data to fine-tune web app performance and experience.

This instructor-led, live training in Norway (online or onsite) targets intermediate developers and software engineers looking to develop AI-driven applications using the LangChain framework.

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

• Grasp the core principles of LangChain and its constituent parts.
• Connect LangChain with large language models (LLMs) such as GPT-4.
• Construct modular AI applications leveraging LangChain.
• Resolve common issues within LangChain applications.

This instructor-led, live training in Norway (online or onsite) is designed for advanced-level data engineers and DevOps professionals who aim to leverage LangChain's capabilities by integrating it 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 Norway (online or onsite) targets 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 is a framework designed for constructing stateful, multi-agent LLM applications by composing graphs that maintain persistent state and allow precise control over execution flow.

This instructor-led training, available both online and on-site, is tailored for intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance.

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

• Design financial LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph state and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems for performance, cost, and SLAs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation 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 for constructing LLM applications with a graph structure, supporting planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (available online or onsite) is designed for beginner-level developers, prompt engineers, and data practitioners aiming to design and build reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and when to use them.
• Build prompt chains that branch, call tools, and maintain memory.
• Integrate retrieval and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph apps for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises on design, testing, and evaluation.

Course Customization Options

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

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 integrate seamlessly with medical workflows.

This instructor-led, live training session (available online or onsite) targets 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 within healthcare production settings.

Format of the Course

• Interactive lectures and discussions.
• Hands-on exercises using 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 arrange.

LangGraph serves as a framework 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 intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.

Upon completing this training, participants will be capable of:

• Designing legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrating legal ontologies and document standards into graph state and processing.
• Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploying, monitoring, and maintaining LangGraph services in production with observability and cost controls.

Course Format

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

Customization Options

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

LangGraph serves as a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.

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

By the end 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, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

• To request a customized training for this course, 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 live training, led by an instructor and available either online or onsite, 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 utilizing conditional logic.
• Integrating LLMs, APIs, and data sources to enable automated personalization.
• Managing state, memory, and context across multi-step campaigns.
• Evaluating, monitoring, and optimizing workflow performance and delivery outcomes.

Course Format

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

Customization Options

• For a customized training session tailored to your needs, please get in touch with us to arrange it.