Vector Databases: Embeddings, Semantic Search, and Hybrid Retrieval

​This is the 3rd 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.

​All events in these series:

1. ​Build Your First RAG Application with LLMs

2. ​From RAG to AI Agents: Function Calling and Tool Use

3. ​Vector Databases: Embeddings, Semantic Search, and Hybrid Retrieval

4. ​RAG and Agents Evaluation: Measuring Retrieval and LLM Answer Quality

5. ​Monitoring LLM Applications: Traces, Feedback, and Production Quality

​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.

​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.​

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