Langchain for beginners : Build GenAI LLM Apps in Easy Steps

About this course

LangChain has quickly become one of the most important frameworks for building real-world applications using large language models (LLMs). This course is designed to help you get started with LangChain and progressively master its powerful features, all through clear and simple examples.

Whether you’re a Python developer, an AI enthusiast, or someone curious about LLMs, this course will give you the tools and confidence to build intelligent applications using both OpenAI and open-source models.

What You’ll Learn

• What LangChain is and how it simplifies integrating LLMs into applications
• Use OpenAI LLMs in Python to generate and process natural language
• Use open-source LLMs like Mistral and Gemma in your own apps
• Run open-source models locally on your machine using Ollama
• Build dynamic prompts using PromptTemplates
• Understand and apply the LangChain Expression Language (LCEL)
• Create simple and regular sequential chains to control workflow logic
• Use multiple LLMs within a single chain for flexible responses
• Maintain and use chat history to create context-aware apps
• Learn about embeddings and apply them to measure text similarity
• Understand vector stores and use them to store and search embeddings
• Learn the Retrieval-Augmented Generation (RAG) workflow
• Implement RAG with your own data using LangChain in simple steps
• Analyze images using multi-modal models
• Understand what Agents are and implement agents
• Use Model Context Protocol (MCP) in your agents to access external tools
• Trace and implement observability your LLM applications using LangSmith
• Build real-world LLM-powered apps using Streamlit and LangChain

Who This Course Is For

• Python developers exploring AI and LLM integration
• Anyone looking to build chatbots, assistants, or smart tools using LLMs
• Professionals working

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