使用 BigQuery 创建嵌入、向量搜索和 RAG

Coursera MOOC / Non-credit USD 49

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使用 BigQuery 创建嵌入、向量搜索和 RAG

About this course

本课程探讨 BigQuery 中用于减轻 AI 幻觉的检索增强生成 (RAG) 解决方案。BigQuery 引入了 RAG 工作流，其中涵盖了创建嵌入、搜索向量空间和生成更优质的回答。本课程解释了这些步骤背后的概念原理，以及这些步骤在 BigQuery 中的实际实施过程。学完本课程后，学员将能够使用 BigQuery 和生成式 AI 模型（如 Gemini）以及嵌入模型来构建 RAG 流水线，以解决在具体情况下遇到的 AI 幻觉问题。

What you'll learn

understand retrieval-augmented generation (RAG) principles
create embeddings
conduct vector space searches
implement RAG workflows in BigQuery

Course objectives

explore AI hallucinations and their mitigation
apply RAG solutions in practical contexts
integrate generative AI models with BigQuery

Skills you'll gain

artificial intelligence machine learning generative ai data analysis rag embeddings vector search bigquery ai data workflows

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