Build a chatbot that answers questions using your own documents with RAG techniques.
Create a question-answering system powered by the ChatGPT API.
Develop an AI agent that can use tools to complete multi-step tasks.
Learn prompt engineering best practices through hands-on coding exercises.
Requires OpenAI API key and Python environment setup with dependencies.
This repository is a Chinese-language learning resource for developers who want to get started building applications with large language models (LLMs). The project is based on a series of courses by Andrew Ng (published in collaboration with OpenAI) and has been translated and adapted into Chinese so that Mandarin-speaking developers can access the material directly, without the access restrictions that apply to the original English versions in some regions. The curriculum covers the full practical workflow of LLM development, from writing effective prompts to building complete chat systems to more advanced topics. Core required courses include prompt engineering for developers, building question-answering systems using the ChatGPT API, and developing applications with LangChain. Optional elective courses extend into RAG (retrieval-augmented generation, a technique for letting a model answer questions based on your own documents), model fine-tuning, and building AI agents with tools. All content is delivered as interactive Jupyter Notebooks. You would use this if you are a Chinese-speaking developer with basic Python skills who wants a structured, hands-on path into practical LLM application development.
Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.