- Large Language Modeling
- Algorithms
- Embeddings
- Generative AI
- Google Cloud Platform
- Semantic Web
- Vector Databases
- Retrieval-Augmented Generation
- Natural Language Processing
Vector Search and Embeddings
Completed by Sunil Srinivasan
March 20, 2024
4 hours (approximately)
Sunil Srinivasan's account is verified. Coursera certifies their successful completion of Vector Search and Embeddings
What you will 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 will gain

