Vector Databases: Embeddings, Semantic Search, and Hybrid Retrieval
Details
This is the 2nd workshop in our series to update the LLM Zoomcamp content.
This workshop updates Module 3: Vector Search.
In this hands-on session, Alexey Grigorev will show how to add semantic search to a RAG application using embeddings and a vector database.
You’ll learn how to turn text into embeddings, index them, search for semantically similar documents, and use the results as context for an LLM.
What you’ll learn:
- What vector search is and how it differs from keyword search
- What embeddings are and how they represent text
- How to embed FAQ documents for semantic retrieval
- How to index text data in a vector database
- How to run semantic search over indexed documents
- How to use vector search inside a RAG pipeline
- How to compare vector search with keyword search
- How hybrid search combines semantic and keyword retrieval
- When vector search works well and where it can fail
- How retrieval quality affects the final LLM answer
By the end, you’ll have a RAG pipeline that uses vector search to retrieve semantically relevant documents and generate answers based on them.
Like the other workshops, this will be a live demo with practical tips and time for Q&A.
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All events in these series:
- Build Your First RAG Application with LLMs
- From RAG to AI Agents: Function Calling and Tool Use
- Vector Databases: Embeddings, Semantic Search, and Hybrid Retrieval
- RAG and Agents Evaluation: Measuring Retrieval and LLM Answer Quality
- Monitoring LLM Applications: Traces, Feedback, and Production Quality
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## Thinking about Joining LLM Zoomcamp?
This workshop covers the updated content for Module 3 of the LLM Zoomcamp, our free course on building practical LLM applications with RAG, vector search, evaluation, monitoring, and AI agents.
You start with a simple RAG pipeline, then improve it with better retrieval, semantic search, function calling, evaluation, monitoring, and production practices.
The course covers the full lifecycle of an LLM application: from the first working prototype to evaluation, monitoring, and a complete final project.
The new cohort of LLM Zoomcamp starts on June 8, 2026. You can join it by registering here.
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## About the Speaker
Alexey Grigorev is the Founder of DataTalks.Club and creator of the Zoomcamp series.
Alexey is a software and ML engineer with over 10 years in engineering and 6+ years in machine learning. He has deployed large-scale ML systems at companies like OLX Group and Simplaex, authored several technical books, including Machine Learning Bookcamp, and is a Kaggle Master with a 1st place finish in the NIPS’17 Criteo Challenge.
**Join our Slack: https://datatalks.club/slack.html**