Boost RAG with Chroma is an intermediate, hands-on course designed for developers and AI practitioners who need to solve one of the biggest challenges with Large Language Models: their tendency to hallucinate. This course moves beyond theory and teaches you how to build a practical, effective Retrieval-Augmented Generation (RAG) pipeline to make your LLMs more trustworthy and enterprise-ready.
Boost RAG with Chroma
您将学到什么
Implement and evaluate a RAG pipeline, using a vector database like Chroma, to reduce LLM hallucinations and measurably improve answer factuality.
您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
本课程是 Chroma, Weaviate & Production RAG Deployment 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有2个模块
In this module, you will build the core of a modern, factual AI system. You'll first learn why even powerful LLMs fail and how the RAG architecture solves this by grounding them in real data. Then, you'll get hands-on experience implementing this pattern to construct a functional pipeline that connects a custom knowledge base directly to an LLM.
涵盖的内容
2个视频1篇阅读材料1个作业1个非评分实验室
With a functional pipeline built, this module focuses on the most critical step: proving its value. You will learn how to systematically test your RAG system, compare its grounded answers against a baseline LLM's responses, and qualitatively evaluate the reduction in hallucinations. This module culminates in a final project where you will formally document your findings.
涵盖的内容
1个视频1篇阅读材料1个作业1个非评分实验室
获得职业证书
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位教师
229 门课程 14,147 名学生
提供方
从 Machine Learning 浏览更多内容
状态：免费试用
状态：免费试用
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