Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.



Vector Search and Embeddings

Instructor: Google Cloud Training
Access provided by Georgetown University
2,811 already enrolled
(18 reviews)
What you'll learn
Explain vector search processes and key technologies.
Construct semantic search using vector embeddings with Vertex AI Vector Search.
Explore grounded agents and retrieval-augmented generation (RAG) to mitigate AI hallucinations.
Create a hybrid search engine with Vertex AI Vector Search.
Skills you'll gain
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There is 1 module in this course
This course introduces Vertex AI Vector Search and describes how it can be used to build a search application with large language model (LLM) APIs for embeddings. The course consists of conceptual lessons on vector search and text embeddings, practical demos on how to build vector search on Vertex AI, and a hands-on lab.
What's included
9 videos1 reading1 assignment2 app items
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Reviewed on Jun 7, 2024
Very interesting course on Vector Search and Embeddings!
Reviewed on Jun 7, 2024
The labs have a lot of waiting for services to spin up (but it gives you time to read and understand more I suppose)
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