Whether delivered online or onsite, instructor-led LangChain training courses illustrate through interactive, practical exercises how to develop AI-driven applications using the LangChain framework.
LangChain training is offered in two formats: "online live training" or "onsite live training." Online live training (also referred to as "remote live training") is conducted via an interactive, remote desktop. Onsite live training can be provided locally at the customer's premises in Sofia or at NobleProg's corporate training centers in Sofia.
NobleProg -- Your Local Training Provider
Crystal Business Center
ул. "Осогово" 40, Sofia, Bulgaria, 1303
Crystal Business Center is located in the central part of Sofia, on the corner of "Osogovo" street. and "Todor Aleksandrov" blvd. The building is easily accessible by metro (only 50 m from Opalchenska station) and other public transport. Its total area is 8000 sq.m. The office area is 6171 sq.m.
This instructor-led, live training in Sofia (online or onsite) is designed for advanced-level AI researchers and policymakers who wish to explore 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 Sofia (online or onsite) is targeted at intermediate-level web developers and UX designers who want to utilize LangChain to build intuitive and user-friendly web applications.
Upon completion of this training, participants will be able to:
Grasp the core concepts of LangChain and its significance in boosting web user experience.
Deploy LangChain within web apps to develop dynamic and responsive interfaces.
Incorporate APIs into web applications to enhance interactivity and user engagement.
Refine user experience through LangChain’s advanced customization capabilities.
Evaluate user behavior data to fine-tune web app performance and overall experience.
This instructor-led, live training in Sofia (online or onsite) is designed for beginner-level business analysts and automation engineers who want to understand how to use LangChain and APIs to automate repetitive tasks and workflows.
Upon completion of this training, participants will be able to:
Grasp the fundamentals of API integration with LangChain.
Automate repetitive workflows using LangChain and Python.
Employ LangChain to connect various APIs for efficient business processes.
Design and automate custom workflows leveraging APIs and LangChain’s automation capabilities.
LangGraph serves as a framework designed to build stateful, multi-agent LLM applications through composable graphs that maintain persistent state and offer precise control over execution.
This instructor-led training, available either online or on-site, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based legal solutions while ensuring necessary compliance, traceability, and governance controls.
Upon completion of this training, participants will be equipped to:
Create legal-specific LangGraph workflows that maintain auditability and compliance.
Incorporate legal ontologies and document standards into graph states and processing.
Implement guardrails, human-in-the-loop approvals, and traceable decision pathways.
Deploy, monitor, and maintain LangGraph services in production environments with effective observability and cost management.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical applications.
Hands-on implementation within a live laboratory environment.
Customization Options
For tailored training on this subject, please contact us to arrange your specific requirements.
This instructor-led, live training in Sofia (online or onsite) is aimed at 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.
LangGraph serves as a framework for constructing stateful, multi-agent LLM applications that operate as composable graphs with persistent state and precise control over execution.
This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based finance solutions that adhere to proper 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 states and tooling.
Implementing reliability, safety, and human-in-the-loop controls for critical processes.
Deploying, monitoring, and optimizing LangGraph systems to ensure performance, cost efficiency, and SLA compliance.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical sessions.
Hands-on implementation within a live-lab environment.
Course Customization Options
To request customized training for this course, please contact us to arrange details.
This instructor-led, live training in Sofia (online or onsite) is aimed at 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.
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 seamlessly align with clinical workflows.
This instructor-led live training (available online or onsite) targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.
Upon completion of this training, participants will be able to:
Design healthcare-specific LangGraph workflows with compliance and auditability as key considerations.
Integrate LangGraph applications with medical ontologies and standards, including 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.
Course Format
Interactive lectures and discussions.
Hands-on exercises featuring 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 make arrangements.
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 online or onsite, targets advanced AI platform engineers, DevOps professionals specializing in AI, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.
By the conclusion of this training, participants will be able to:
Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
Ensure reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
Debug and trace graph executions, inspect state changes, and systematically reproduce production issues.
Instrument graphs with logs, metrics, and traces; deploy them to production; and monitor SLAs and costs.
Format of the Course
Interactive lectures and discussions.
Extensive exercises and practical practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request customized training for this course, please contact us to arrange it.
This guided, live training session in Sofia (delivered online or onsite) is designed for intermediate-level professionals looking to deepen their knowledge of conversational agents and apply LangChain to real-world scenarios.
By the conclusion of this training, participants will be able to:
Comprehend the foundational concepts of LangChain and its role in constructing conversational bots.
Create and deploy conversational agents using LangChain.
Link conversational agents with APIs and external services.
Implement Natural Language Processing (NLP) methods to boost the performance of conversational agents.
This instructor-led, live training in Sofia (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.
LangGraph is a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving Large Language Models (LLMs) and various tools. It is particularly well-suited for automating and personalizing content pipelines.
This instructor-led live training, available both online and onsite, targets intermediate-level marketers, content strategists, and automation developers looking to build dynamic, branching email campaigns and content generation pipelines using LangGraph.
Upon completion of this training, participants will be equipped to:
Create graph-structured workflows for emails and content that incorporate conditional logic.
Connect LLMs, APIs, and data sources to enable automated personalization.
Manage state, memory, and context throughout multi-step campaigns.
Assess, monitor, and optimize the performance and delivery results of workflows.
Course Format
Interactive lectures accompanied by group discussions.
Practical labs focused on implementing email workflows and content pipelines.
Scenario-based exercises covering personalization, segmentation, and branching logic.
Course Customization Options
To arrange a customized version of this training, please contact us.
This instructor-led live training in Sofia (online or on-site) is designed for beginner to intermediate developers and software engineers who aim to learn the core concepts and architecture of LangChain and gain the practical skills necessary 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).
LangGraph is a framework designed for composing graph-structured workflows involving LLMs, enabling features such as branching, tool usage, memory management, and controllable execution.
This instructor-led, live training (available online or onsite) targets intermediate-level engineers and product teams looking to integrate LangGraph’s graph logic with LLM agent loops to create dynamic, context-aware applications. Examples include customer support agents, decision trees, and information retrieval systems.
Upon completing this training, participants will be capable of:
Designing graph-based workflows that effectively coordinate LLM agents, tools, and memory.
Implementing conditional routing, retries, and fallback mechanisms to ensure robust execution.
Integrating retrieval mechanisms, APIs, and structured outputs into agent loops.
Evaluating, monitoring, and hardening agent behavior to enhance 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 Customization Options
To request a customized training session for this course, please contact us to arrange.
This instructor-led, live training in Sofia (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build 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.
LangGraph is a specialized framework designed for constructing LLM applications with a graph-based architecture. It facilitates advanced capabilities such as planning, branching logic, tool utilization, memory management, and controllable execution flows.
This instructor-led live training, available both online and onsite, is tailored for 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 equipped to:
Articulate core LangGraph concepts, including nodes, edges, and state, and understand appropriate use cases.
Construct prompt chains that support branching, tool invocation, and persistent memory.
Integrate retrieval mechanisms and external APIs into graph-based workflows.
Test, debug, and evaluate LangGraph applications to ensure reliability and safety.
Course Format
Interactive lectures coupled with facilitated discussions.
Guided laboratory exercises and code walkthroughs within a sandbox environment.
Scenario-based exercises focusing on design, testing, and evaluation strategies.
Customization Options
For requests regarding customized training for this course, please contact us to arrange suitable arrangements.
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