datawhalechina

    datawhalechina/llm-cookbook

    面向开发者的 LLM 入门教程,吴恩达大模型系列课程中文版

    llm
    cookbook
    Jupyter Notebook
    24.9K stars
    3.0K forks
    179 GitHub watchers
    Updated Nov 10, 2026
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    Where it stands

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    The project lists 37 contributors on GitHub.

    Use Cases & Benefits

    • Provides a comprehensive Chinese-language LLM tutorial series based on Andrew Ng's large model courses, including code examples and practical exercises.
    • Delivers localized, accessible, and systematically organized LLM learning content tailored for Chinese developers with bilingual code and prompts.
    • Use for developers with basic Python skills to quickly learn foundational LLM concepts and prompt engineering in a Chinese context.
    • Use for building practical LLM applications such as ChatGPT-based Q&A systems and LangChain-powered personalized AI tools.
    • Use for exploring advanced LLM topics like model fine-tuning, retrieval-augmented generation, and generative AI UI development with Gradio.

    Should you depend on it?

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    License

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    Community files

    • README: present

    Watch-outs

    • Warning: No license file detected by GitHub: unless the project grants one elsewhere, you generally have no permission to use, modify or distribute the code.
    • Warning: No commits in over a year (last push Jun 2025).

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    From the README

    本项目是一个面向开发者的大模型手册,针对国内开发者的实际需求,主打 LLM 全方位入门实践。本项目基于吴恩达老师大模型系列课程内容,对原课程内容进行筛选、翻译、复现和调优,覆盖从 Prompt Engineering 到 RAG 开发、模型微调的全部流程,用最适合国内学习者的方式,指导国内开发者如何学习、入门 LLM 相关项目。

    针对不同内容的特点,我们对共计 11 门吴恩达老师的大模型课程进行了翻译复现,并结合国内学习者的实际情况,对不同课程进行了分级和排序,初学者可以先系统学习我们的必修类课程,掌握入门 LLM 所有方向都需要掌握的基础技能和概念,再选择性地学习我们的选修类课程,在自己感兴趣的方向上不断探索和学习。

    如果有你非常喜欢但我们还没有进行复现的吴恩达老师大模型课程,我们欢迎每一位开发者参考我们已有课程的格式和写法来对课程进行复现并提交 PR,在 PR 审核通过后,我们会根据课程内容将课程进行分级合并。欢迎每一位开发者的贡献!

    在线阅读地址:面向开发者的 LLM 入门课程 - 在线阅读

    PDF 下载地址:面向开发者的 LLM 入门教程 - PDF

    英文原版地址:吴恩达关于大模型的系列课程

    LLM 正在逐步改变人们的生活,而对于开发者,如何基于 LLM 提供的 API 快速、便捷地开发一些具备更强能力、集成 LLM 的应用,来便捷地实现一些更新颖、更实用的能力,是一个急需学习的重要能力。

    由吴恩达老师与 OpenAI 合作推出的大模型系列教程,从大模型时代开发者的基础技能出发,深入浅出地介绍了如何基于大模型 API、LangChain 架构快速开发结合大模型强大能力的应用。其中,《Prompt Engineering for Developers》教程面向入门 LLM 的开发者,深入浅出地介绍了对于开发者,如何构造 Prompt 并基于 OpenAI 提供的 API 实现包括总结、推断、转换等多种常用功能,是入门 LLM 开发的经典教程;《Building Systems with the ChatGPT API》教程面向想要基于 LLM 开发应用程序的开发者,简洁有效而又系统全面地介绍了如何基于 ChatGPT API 打造完整的对话系统;《LangChain for LLM Application Development》教程结合经典大模型开源框架 LangChain,介绍了如何基于 LangChain 框架开发具备实用功能、能力全面的应用程序,《LangChain Chat With Your Data》教程则在此基础上进一步介绍了如何使用 LangChain 架构结合个人私有数据开发个性化大模型应用;《Building Generative AI Applications with Gradio》、《Evaluating and Debugging Generative AI》教程分别介绍了两个实用工具 Gradio 与 W&B,指导开发者如何结合这两个工具来打造、评估生成式 AI 应用。

    Excerpt from the datawhalechina/llm-cookbook README on GitHub. © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Forks

    3.0K+36

    Open issues

    11+1

    Compared with peers in LLM

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth

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