|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/lamaindex/
课程评论：没有评论
LlamaIndex 库 LLM 应用开发（旧版，V0.8.48） 本课程专为有软件工程背景和 Python 熟练度的学习者设计，旨在教授如何快速利用 LlamaIndex 库开发 LLm_POWERED 的应用程序。课程将从零开始，通过构建一个“文档助手”项目，创建一个能够处理 Python 包文档（或其他数据）的聊天机器人，来深入讲解 LlamaIndex 的核心概念和技术。 **课程内容包括：** * **LlamaIndex 核心功能：** 深入理解 LlamaIndex 的工作原理。 * **检索增强生成 (RAG)：** 学习如何结合检索和生成技术。 * **向量存储：** 重点介绍 Pinecone 向量数据库的使用。 * **节点解析器 (Node Parsers) / 文本分割器 (TextSplitters)：** 掌握数据预处理和分块技术。 * **查询引擎 (QueryEngines) 和聊天引擎 (ChatEngines)：** 构建与 LLM 交互的接口。 * **Streamlit：** 实现用户界面，方便展示和交互。 * **Agent 和 LLM 推理：** 学习构建智能代理，并理解 LLM 的推理能力。 * **ReAct 框架：** 应用 ReAct 模式提升 LLM 的推理和行动能力。 * **输出解析器 (Output Parsers)：** 规范和处理 LLM 的输出。 * **LLMs：** 学习少样本提示 (Few-shot prompting)、思维链 (Chain of Thought) 和 ReAct 提示等高级提示工程技术。 **项目成果：** * 构建一个“文档助手”聊天机器人。 **课程特色：** * **实操驱动：** 通过动手练习和真实项目巩固知识。 * **社区支持：** 提供一对一故障排除支持、GitHub 资源链接、FAQ、故障排除指南以及专属 Discord 社区。 * **持续更新：** 课程内容将免费获得更新和改进。 **重要提示：** * 本课程内容基于 LlamaIndex 版本 **v0.8.48**，可能与最新版本存在差异。 * 课程假设学习者具备扎实的软件工程基础和 Python 编程能力。 * IDE（如 Pycharm/VSCode）仅用于调试和运行脚本，不依赖 IDE 的高级功能。
Welcome to first LlamaIndex Udemy course - Unleashing the Power of LLM!This comprehensive course is designed to teach you how to QUICKLY harness the power the LlamaIndex library for LLM applications. This course will equip you with the skills and knowledge necessary to develop cutting-edge LLM solutions for a diverse range of topics.Disclaimer: This course is not up to date with the latest version of LlamaIndex and uses first-party models for the implementations. Please ensure you are aware of the version differences when following along.Course was filmed on version: "==0.8.48"Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in PythonIn this course, you will embark on a journey from scratch to building a real-world LLM powered application using LlamaIndex. We are going to do so by build the main application:Documentation Helper- Create chatbot over a python package documentation. (and over any other data you would like)The topics covered in this course include:LlamaIndexRetrieval Augmentation GenerationVectorstores (Pinecone)Node Parers- TextSplittersQueryEngines, ChatEnginesStreamlit (for UI)Agents, LLM ReasoningReActOutput ParsersLLMs: Few shots prompting, Chain of Thought, ReAct promptingThroughout the course, you will work on hands-on exercises and real-world projects to reinforce your understanding of the concepts and techniques covered. By the end of the course, you will be proficient in using LlamaIndex to create powerful, efficient, and versatile LLM applications for a wide array of usages.This is not just a course, it's also a community. Along with lifetime access to the course, you'll get:Dedicated 1 on 1 troubleshooting support with meGithub links with additional AI resources, FAQ, troubleshooting guidesAccess to an exclusive Discord community to connect with other learners No extra cost for continuous updates and improvements to the courseDISCLAIMERSPlease note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python. I will be using Pycharm/ VSCode IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts.
