LLM Application Fundamentals with LangChain

You will build a complete, functioning Gen AI application from scratch — from understanding the architecture and setting up LangChain, through creating prompt templates and model interfaces, to building a Gradio UI — giving you a hands-on feel for what AI engineering involves.

You will learn to build practical LLM applications from the ground up — from setting up authentication and importing LangChain, through validating user inputs and parsing structured outputs, to implementing comprehensive error handling — enabling you to create robust, production-ready applications that safely integrate LLMs into real-world workflows.

You will learn to build conversational AI applications that maintain context across multiple exchanges — from understanding message structures and designing chatbot prompts, through implementing conversation logic and UI with Gradio, to persisting conversations in databases — enabling you to create interactive, stateful chatbots that provide natural back-and-forth interactions.

You will learn to implement streaming for real-time response delivery in conversational applications — from understanding token-based streaming and Python yield generators to building stream handlers in UI — enabling you to deliver responsive chatbots with immediate, incremental output.