LangChain for LLM Application Development

It's concise and hands-on, ideal for a developer who wants a quick, practical first look at LangChain rather than an in-depth course; you'll need to code Python, and running the examples uses model APIs billed separately by the provider. One genuinely useful thing to know before paying anything: this is a DeepLearning.AI short course, and the identical course is available free on the DeepLearning.AI website — so on Coursera you can audit it free, or take it free at the source, and only pay if you specifically want the Coursera certificate (a subscription, about $49/month, or Coursera Plus). LangChain evolves rapidly, so check the methods match the current version (as of 2026).

LangChain for LLM Application Development is a one-hour guided project that moves fast through the core LangChain building blocks: calling LLMs with prompts and parsing responses, adding memory so conversations have context, chaining operations together, answering questions over your own documents, and a first look at agents as reasoning engines. It's taught by Harrison Chase, who created LangChain, alongside Andrew Ng.