LangChain for Data Analysis and Visualization Training Course

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

This instructor-led live training, available either online or on-site, is tailored for advanced AI platform engineers, DevOps professionals specializing in AI, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.

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

• Design and optimize intricate LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Enhance reliability through 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 practice.
• Hands-on implementation within a live lab environment.

Customization Options

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

This instructor-led live training in Turkey (online or onsite) targets developers and IT professionals of all skill levels who wish to leverage AI for automating tasks and processes with minimal coding.

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 Turkey (online or onsite) targets beginner-level business analysts and automation engineers who wish to learn how to use LangChain and APIs for automating repetitive tasks and workflows.

By the conclusion of 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.
• Develop and automate custom workflows by combining APIs with LangChain’s automation features.

This instructor-led, live training in Turkey (online or onsite) targets intermediate-level professionals who aim 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 Turkey (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 Turkey (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 live, instructor-led training in Turkey (online or on-site) is designed for intermediate-level developers and software engineers who aim to build AI-powered applications using the LangChain framework.

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

• Understand the fundamental principles and components of LangChain.
• Connect LangChain with large language models (LLMs) such as GPT-4.
• Develop modular AI applications using LangChain.
• Troubleshoot typical issues found in LangChain applications.

This instructor-led, live training in Turkey (online or on-site) is designed for advanced-level data engineers and DevOps professionals who wish 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 Turkey (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the 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-actor LLM applications by composing graphs that maintain persistent state and allow precise control over execution flow.

This instructor-led live training, available either online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage finance solutions based on LangGraph, ensuring proper governance, observability, and regulatory compliance.

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

• Designing LangGraph workflows tailored to financial regulations and audit requirements.
• Integrating financial data standards and ontologies into graph states and tools.
• Implementing reliability, safety measures, 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

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

LangGraph is a framework designed for constructing graph-structured Large Language Model (LLM) applications that support planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (available online or on-site) targets beginner-level developers, prompt engineers, and data practitioners who want to design and build reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and understand when to apply them.
• Build prompt chains that branch, invoke tools, and maintain memory.
• Integrate retrieval mechanisms and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph applications to ensure 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 customized training for this course, please contact us to arrange.

LangGraph empowers stateful, multi-agent 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 seamlessly align with clinical workflows.

This instructor-led live training, available online or on-site, 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 completion of this training, participants will be equipped to:

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

Course Format

• Interactive lectures and discussions.
• Hands-on exercises featuring real-world case studies.
• Implementation practice within a live laboratory environment.

Customization Options

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

LangGraph serves as a framework designed for constructing stateful, multi-agent 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 intermediate to advanced professionals aiming 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:

• Crafting legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrating legal ontologies and document standards into graph state and processing mechanisms.
• Implementing guardrails, human-in-the-loop approvals, 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 practice.
• Hands-on implementation within a live lab environment.

Customization Options for the Course

• To request customized training for this course, please get in touch with us to arrange details.

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 (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.

Course Format

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

Customization Options

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

LangGraph is a graph-based orchestration framework that supports 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 looking 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.