Vector Search and Embeddings

Vector Search and Embeddings

Instructor: Google Cloud Training

Access provided by Willis Towers Watson

3,273 already enrolled

1 module

Gain insight into a topic and learn the fundamentals.

19 reviews

Intermediate level

Some related experience required

4 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

19 reviews

Intermediate level

Some related experience required

4 hours to complete

Flexible schedule

Learn at your own pace

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

Tools you'll learn

Details to know

Shareable certificate

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Assessments

1 assignment

Taught in English

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There is 1 module in this course

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.

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.