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所在平台: Udemy |
课程主页: https://www.udemy.com/course/agentic-ai-deliver-a-successful-chatbot-poc-with-langgraph/
课程评论：没有评论
**课程总结：Agentic AI：使用 LangGraph 交付成功的聊天机器人 PoC** 本课程旨在帮助学员掌握将先进的 AI 技术（包括大型语言模型、RAG、LangGraph 和 Agentic AI）融会贯通，并将其应用于构建实际可用的聊天机器人概念验证 (PoC) 的能力。课程重点不在于孤立地学习各项技术，而是强调如何在实际项目流程中将它们结合起来，并聚焦于做出务实的决策、应对真实世界的挑战、注重生产就绪性，最终将技术转化为功能性产品。 **课程内容概述：** 本课程将模拟一个面向客户的聊天机器人 PoC 项目。学员将学习如何从项目范围界定、架构设计、实现到交付的全过程，使用 LLM 和 LangGraph 技术，同时充分考虑实际的约束条件和挑战。课程将涵盖项目范围界定、架构设计、实现以及生产就绪的关键因素，重点在于如何创建一个功能齐全且具有说服力的聊天机器人。 **课程要求：** 本课程并非入门级课程。学员需要具备一定的软件工程项目功能和技术方面的知识背景，以最大化学习效果。同时，学员应对 LangGraph 有基本的了解，但无需成为专家。 **免责声明：** 本课程内容仅供教育和信息参考。课程内容基于创建时的知识。尽管已尽一切努力确保准确性，但讲师不对所提供信息的完整性、可靠性或适用性做任何明示或暗示的保证。此外，本课程可能引用第三方工具、框架或服务，这些引用不构成认可，讲师对这些外部资源的任何变更、限制或问题概不负责。报名参加本课程即表示您承认并同意这些条款。
Motivation This course is about understanding the technology and applying it to build something meaningful. Instead of just learning how LLMs, RAG, LangGraph and agentic AI work in isolation, you'll see how they come together in the scope of a chatbot proof of concept (PoC). The focus is on making practical decisions, handling real-world challenges, keeping an eye towards production readiness and turning technologies into something functional.ScopeIn this course, we will simulate a scenario where a hypothetical client has requested a chatbot PoC. Our goal is to specify, design, build, and deliver this PoC using LLMs and LangGraph while considering practical constraints and challenges. We will cover project scoping, architecture, implementation, and key factors for production readiness, focusing on what it takes to create a functional and presentable chatbot.What this course is notThis is not a beginner-level course. Some exposure to functional and technical aspects of a software engineering project is required to help you get the most out of it.This is not a comprehensive LangGraph course, but some basic familiarity will suffice. DisclaimerThis course is for educational and informational purposes only. The content provided is based on knowledge at the time of creation. While every effort has been made to ensure accuracy, the instructor makes no guarantees, express or implied, about the completeness, reliability, or applicability of the information presented. Additionally, this course may reference third-party tools, frameworks, or services. These references do not imply endorsement, and the instructor is not responsible for any changes, limitations, or issues related to such external resources. By enrolling in this course, you acknowledge and agree to these terms.
