LangChain Training Course

The LangChain Training Course from The Hub of Knowledge is designed for developers, AI engineers, and technology professionals who want to build advanced AI-powered applications using the LangChain framework.

This hands-on training covers LangChain architecture, chains, agents, memory, Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, API integrations, and deployment of enterprise AI applications. Participants will learn how to create intelligent AI systems powered by Large Language Models (LLMs).

The LangChain Training Course provides practical knowledge to design and deploy AI-driven applications using Large Language Models and LangChain orchestration frameworks. The course focuses on real-world implementation and enterprise AI use cases.

Delegates will gain experience with:

• LangChain fundamentals
• Prompt engineering
• AI chains & workflows
• AI agents & tools
• Memory systems
• RAG architecture
• Vector databases
• OpenAI integrations
• LLM deployment strategies
• Enterprise AI automation

Module 1: Introduction to LangChain

• Understanding LangChain Framework
• Generative AI & LLM Overview
• LangChain ecosystem architecture
• LangChain use cases
• Setting up development environment

Module 2: Prompt Engineering with LangChain

• Prompt templates
• Dynamic prompting
• Few-shot prompting
• Output parsers
• Prompt optimization strategies

Module 3: LangChain Chains

• Simple chains
• Sequential chains
• Multi-step workflows
• Data processing pipelines
• Custom chain development

Module 4: LangChain Memory

• Conversation memory
• Buffer memory
• Summary memory
• Context handling
• Stateful AI applications

Module 5: AI Agents & Tool Usage

• Understanding LangChain Agents
• Agent architectures
• Tool integrations
• Autonomous workflows
• Multi-agent orchestration

Module 6: Retrieval-Augmented Generation (RAG)

• RAG architecture
• Document loaders
• Text splitting & chunking
• Embeddings generation
• Context-aware AI systems

Module 7: Vector Databases Integration

• Pinecone integration
• FAISS implementation
• Chroma DB
• Semantic search systems
• Similarity search applications

Module 8: OpenAI & LLM Integrations

• OpenAI API integration
• Hugging Face integration
• Llama models
• Claude & Gemini integrations
• Multi-model AI applications

Module 9: Building AI Applications

• AI chatbots
• Knowledge assistants
• Document Q&A systems
• AI automation workflows
• Enterprise AI solutions

Module 10: Deployment & Production

• Deploying LangChain applications
• API deployment
• Docker containerization
• Monitoring & scaling
• Security & governance

Capstone Project

• Build a complete AI chatbot
• Create a RAG-powered assistant
• Deploy enterprise-grade LangChain application