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Create Embeddings, Vector Search, and RAG with BigQuery

This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations.

Advanced
25m
(1)

Created by Google Cloud

Last Updated Jan 30, 2025

Course Thumbnail
  • Course

Create Embeddings, Vector Search, and RAG with BigQuery

This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations.

Advanced
25m
(1)

Created by Google Cloud

Last Updated Jan 30, 2025

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This course is included in the libraries shown below:

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  • Data
What you'll learn

This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.

Create Embeddings, Vector Search, and RAG with BigQuery
Advanced
25m
(1)
Table of contents

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Google Cloud - Pluralsight course - Create Embeddings, Vector Search, and RAG with BigQuery
Google Cloud
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