Building Conversational Agents with LangChain Training Course

LangGraph serves as a framework for developing stateful, multi-agent LLM applications through composable graphs that maintain persistent state and allow precise control over execution flow.

This instructor-led live training, available both online and onsite, is tailored for advanced-level AI platform engineers, AI DevOps specialists, and ML architects aiming 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 improve scalability.
• Building 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 to production; and monitoring SLAs and costs.

Course Format

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

Customization Options

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

This instructor-led, live training in Malaysia (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 Malaysia (online or onsite) is aimed at 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:

• Understand the basics 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 Malaysia (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 Malaysia (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.
• Optimise user experience using LangChain’s advanced customisation features.
• Analyse user behaviour data to fine-tune web app performance and experience.

This instructor-led live training in Malaysia (online or onsite) is designed for intermediate-level developers and software engineers seeking to build AI-powered applications using the LangChain framework.

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

• Understand the foundational aspects of LangChain and its components.
• Integrate LangChain with large language models (LLMs) like GPT-4.
• Construct modular AI applications using LangChain.
• Troubleshoot typical issues encountered in LangChain applications.

This instructor-led live training in Malaysia (online or onsite) is designed for advanced data engineers and DevOps professionals who wish to leverage LangChain’s capabilities by integrating it with various cloud services.

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

• Integrate LangChain with major cloud platforms including AWS, Azure, and Google Cloud.
• Leverage cloud-based APIs and services to enhance applications powered by LangChain.
• Scale and deploy conversational agents to the cloud for real-time interactions.
• Implement monitoring and security best practices within cloud environments.

This instructor-led, live training in Malaysia (online or on-site) is intended for intermediate-level data professionals who wish to use LangChain to enhance their data analysis and visualization capabilities.

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

• Automate data retrieval and cleaning using LangChain.
• Conduct advanced data analysis using Python and LangChain.
• Create visualizations with Matplotlib and other Python libraries integrated with LangChain.
• Leverage LangChain for generating natural language insights from data analysis.

This instructor-led, live training in Malaysia (online or onsite) targets beginner to intermediate-level developers and software engineers eager to master the core concepts and architecture of LangChain, equipping them with the practical skills needed to build AI-powered applications.

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

• Comprehend the foundational principles of LangChain.
• Set up and configure the LangChain environment.
• Understand the architecture and the way LangChain interacts with large language models (LLMs).
• Develop straightforward applications using LangChain.

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

This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance measures.

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

• Design finance-specific 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 to meet performance, cost, and SLA objectives.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice.
• 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 designed for constructing graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (available online or onsite) is tailored for beginner-level developers, prompt engineers, and data practitioners who wish 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 empowers 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, interoperability, and the development of decision-support systems that seamlessly align with medical workflows.

This instructor-led live training session is available both online and onsite. It is designed for intermediate to advanced-level professionals aiming 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 that prioritize compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards such as 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.

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 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 online or onsite) targets intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based legal solutions equipped with necessary compliance, traceability, and governance controls.

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

• Design legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrate legal ontologies and document standards into graph state and processing workflows.
• Implement guardrails, human-in-the-loop approvals, and traceable decision paths.
• Deploy, monitor, and maintain LangGraph services in production environments with robust observability and cost controls.

Course Format

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

Customization Options

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

LangGraph is 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) is aimed at 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 is a graph-based orchestration framework designed to enable conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalizing content pipelines.

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

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

• Design graph-structured content and email workflows incorporating conditional logic.
• Integrate LLMs, APIs, and data sources to facilitate automated personalization.
• Manage state, memory, and context throughout 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 customized training for this course, please contact us to arrange a session.