- Vector Databases
- Large Language Modeling
- Embeddings
- Google Cloud Platform
- Generative AI
- Retrieval-Augmented Generation
- Algorithms
- Natural Language Processing
- Semantic Web
Vector Search and Embeddings
Completed by Michal Vareka
March 1, 2024
4 hours (approximately)
Michal Vareka'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
