What will you in LangChain- Develop LLM powered applications with LangChain Course
Build three end‑to‑end LangChain-powered LLM applications in Python.
Apply prompt engineering techniques (chain-of-thought, ReAct, few-shot) within real workflows.
Integrate components: chains, agents, document loaders, memory, and callback functions.
Implement Retrieval‑Augmented Generation (RAG) with vector stores like Pinecone and FAISS.
Navigate LangChain’s expression language and dive into its open-source codebase.
Program Overview
Module 1: Introduction to LangChain & Model Setup
⏳ 30 minutes
Understand the framework architecture and required Python environment.
Walk through basic LangChain setup with API keys and model configuration.
Module 2: Chains, Prompt Templates & Basic Apps
⏳120 minutes
Learn chains structure, prompt templates, and input/output mapping.
Build first real-world LangChain app using OpenAI LLM.
Module 3: Memory & Document Loaders
⏳90 minutes
Integrate memory to maintain conversation context across sessions.
Load data (PDF, text) into your app and manage document ingestion.
Module 4: RAG & Vector Databases
⏳90 minutes
Implement RAG pipelines using Pinecone and FAISS.
Set up embeddings, similarity search, and semantic retrieval logic.
Module 5: Agents, Callbacks & LCEL
⏳90 minutes
Design multi-step agents capable of API calls and Python execution.
Learn about callbacks and experiment with LangChain’s expression language.
Module 6: Review, Debugging & Real-world Integration
⏳60 minutes
Analyze your deployed apps, debug chains, and optimize performance.
Review best practices and how to extend your project further.
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Job Outlook
High Demand: LangChain skills are essential for roles in AI product development and LLM engineering.
Career Advancement: Useful for software engineers transitioning into GenAI app development.
Salary Potential: $100K–$180K+ for roles involving LLM workflows and AI services.
Freelance Opportunities: Building chatbots, document-based assistants, and RAG-powered tools for clients.
Specification: LangChain- Develop LLM powered applications with LangChain
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