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LangChain Mastery Workshop
Build Real-World GenAI Applications with LangChain and Vector Intelligence
The LangChain Mastery Workshop by NextAgile is an intensive, developer-focused program designed to help technical teams build scalable Generative AI applications using LangChain, vector databases, and RAG architectures.
This practitioner-led workshop enables participants to move from AI experimentation to production-ready implementation—empowering enterprises to create secure, domain-aware, and contextually intelligent solutions.
Hands-on. Production-ready. Enterprise-focused.
Trusted By Global Leaders
Program Overview
As enterprises adopt Generative AI, one of the biggest challenges lies in bridging the gap between experimentation and scalable application development.
This program provides a practical, end-to-end learning journey on how to architect, develop, and deploy LangChain-based applications integrated with vector databases and APIs.
Participants will gain deep insights into:
LangChain Foundations
Learn how to orchestrate LLMs, tools, and memory components for dynamic workflows.
Retrieval-Augmented Generation (RAG)
Build context-aware AI using vector stores like FAISS, Weaviate, or Qdrant.
Real-World Application Design
Translate GenAI concepts into working prototypes and deployable enterprise solutions.
The workshop blends live coding, case studies, and guided mini projects to ensure practical understanding and enterprise applicability.
Enterprise Objectives
This workshop strengthens enterprise capability in AI application engineering, RAG architecture, and data-driven decision systems. By equipping teams with practical LangChain development experience, organizations can:
- Build internal AI copilots and assistants using proprietary data.
- Build in-house GenAI capabilities to reduce dependency on external AI tool.
- Accelerate POCs and MVPs for GenAI-driven products.
- Enhance automation, knowledge discovery, and contextual search efficiency.
Program Structure
The LangChain Mastery Workshop combines guided instruction, live coding, and hands-on practice to help participants translate concepts into real-world AI development.
Each module progressively builds technical fluency and application confidence—culminating in a working GenAI solution by the end of the workshop.
- Duration - 42 Hours (customizable for corporate needs)
- Mode - Live Online / In-Person / Hybrid (as per corporate preference)
- Hands-on Learning - Hands-on, Project based learning
Course Outline
- Chain types, agents, and tools
- Memory and retrieval augmented generation
- Using FAISS, Weaviate, Qdrant
- Chunking, embedding, and retrieval
- Plugging into search engines, docs, APIs
- Design and implement a multi-turn GenAI app
- Use case walkthrough. E.g. Support bot
- Individual or group work on building a custom GenAI workflow
Who Should Participate?
This workshop is ideal for:
Application Developers integrating LLMs into existing systems.
Backend Engineers building scalable GenAI pipelines.
AI/ML Architects designing data-aware and secure AI workflows.
Technical Product Teams exploring enterprise-grade AI use cases.
Business Outcomes
After completing the program, teams will be able to:
After completing the program, teams will be able to
- Design and deploy LLM-powered enterprise applications.
- Build and optimize RAG pipelines for contextual AI retrieval.
- Integrate APIs, databases, and internal data with LLMs.
- Rapidly prototype and deliver AI-driven business solutions.
- Strengthen internal AI engineering capability and reduce time-to-deployment.
Participants Will Learn
- How to design, build, and deploy custom GenAI apps using LangChain.
- Techniques to connect LLMs with APIs, databases, and internal tools.
- Methods to manage memory, chains, and agents for real-world use cases.
- Best practices for optimizing performance, scalability, and data security in GenAI systems.
Why Partner with NextAgile?
- Practitioner-led sessions led by experts in real-world GenAI implementation.
- Enterprise-aligned curriculum customized to your architecture, data, and AI roadmap.
- Use case-driven approach ensuring immediate business relevance and applicability.
- Hands-on mini projects focused on internal data and domain-specific solutions.
- Post-workshop enablement to guide teams from learning to real-world deployment.
Frequently Asked Questions
No. A working knowledge of coding and APIs is sufficient. The course builds GenAI concepts step-by-step from fundamentals to application.
It’s hands-on, enterprise-aligned, and focuses on LangChain engineering and RAG workflows—not theory or tool overviews.
Yes. Each participant or team builds a custom LangChain project, such as a document Q&A assistant or retrieval-based chatbot.
Absolutely. The program can integrate your data sources, APIs, or specific domains for maximum organizational relevance.
42 hours (flexible), delivered online, onsite, or hybrid, depending on enterprise needs.
From Code to Context — Master LangChain for Real-World AI
Equip your teams to build scalable, secure, and domain-aware GenAI applications.
