- 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
- 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
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This course is included in the libraries shown below:
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- Data
What you'll learn
This course content has now been retired on Pluralsight and will be removed by the end of 2026
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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
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