LangChain Fundamentals Training Course

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

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

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

• Design and optimize complex LangGraph topologies for speed, cost-efficiency, and scalability.
• Enhance reliability through retries, timeouts, idempotency, and checkpoint-based recovery.
• Debug and trace graph executions, inspect state, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces; deploy to production; and monitor SLAs and costs.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical 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.

This instructor-led, live training in Botswana (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 Botswana (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:

• Understand 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 Botswana (online or onsite) is aimed at intermediate-level professionals who wish to deepen their understanding of conversational agents and apply LangChain to real-world use cases.

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

• Understand the fundamentals of LangChain and its application in building conversational agents.
• Develop and deploy conversational agents using LangChain.
• Integrate conversational agents with APIs and external services.
• Apply Natural Language Processing (NLP) techniques to improve the performance of conversational agents.

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

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

• Grasp the fundamental concepts of LangChain and its significance in enhancing web user experience.
• Implement LangChain within web apps to develop dynamic and responsive interfaces.
• Integrate APIs into web applications to bolster interactivity and user engagement.
• Optimize user experience through LangChain’s advanced customization features.
• Analyze user behavior data to refine web app performance and experience.

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

By the conclusion 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 Botswana (online or onsite) is designed for advanced data engineers and DevOps professionals who want 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.
• Utilise 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 within cloud environments.

This instructor-led, live training in Botswana (online or in-person) targets intermediate-level data professionals seeking to utilise LangChain to enhance their data analysis and visualisation skills.

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

• Automate data retrieval and cleansing using LangChain.
• Execute advanced data analysis using Python and LangChain.
• Produce visualisations with Matplotlib and other Python libraries integrated with LangChain.
• Employ LangChain to generate natural language insights from data analysis.

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

This instructor-led, live training—available both online and onsite—is designed for intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based finance solutions with appropriate 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 state and tooling.
• Implementing 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 sessions.
• Hands-on implementation within a live-lab environment.

Customization Options

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

LangGraph is a framework designed for creating graph-structured Large Language Model (LLM) applications that facilitate planning, branching, tool utilisation, memory management, and controlled execution.

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

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

• Explaining core LangGraph concepts (nodes, edges, state) and determining when to apply them.
• Constructing prompt chains that branch, invoke tools, and retain memory.
• Integrating retrieval mechanisms and external APIs into graph workflows.
• Testing, debugging, and evaluating LangGraph applications for reliability and safety.

Format of the Course

• Interactive lectures and facilitated discussions.
• Guided labs and code walkthroughs within a sandbox environment.
• Scenario-based exercises focusing 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 LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, achieving interoperability, and developing decision-support systems that align with clinical workflows.

This instructor-led training, available online or onsite, is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.

Upon completing this training, participants will be able to:

• Design healthcare-specific LangGraph workflows that prioritise 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 lectures and discussions.
• Hands-on exercises using real-world case studies.
• Implementation practice in a live laboratory environment.

Course Customization Options

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

LangGraph serves as a framework for developing stateful, multi-actor LLM applications through composable graphs that feature 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 operate LangGraph-based legal solutions equipped with the necessary compliance, traceability, and governance controls.

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

• Designing legal-specific LangGraph workflows that maintain 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 environments with observability and cost controls.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• 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 composing graph-structured LLM workflows that facilitate branching, tool utilisation, memory management, and controllable execution.

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

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

• Design graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallbacks to ensure robust execution.
• Integrate retrieval mechanisms, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behaviour to guarantee 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 Customisation Options

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

LangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured content and email workflows with conditional logic.
• Integrate LLMs, APIs, and data sources for automated personalization.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimize workflow performance and delivery outcomes.

Format of the Course

• Interactive lectures and group discussions.
• Hands-on labs implementing email workflows and content pipelines.
• Scenario-based exercises on personalization, segmentation, and branching logic.

Course Customization Options

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