Want to learn how to build an AI system that answers questions about your knowledge base? 

We’re excited to announce our partnership with Alexey Grigorev and DataTalks.Club to bring you a free, hands-on, 10-week course focused on building real-life applications of LLMs. 

Gain hands-on experience with LLMs, RAG, vector search, evaluation, monitoring, and more.

## Learn RAG and Vector Search
In this course, you'll learn how to create an AI system that can answer questions about your own knowledge base using LLMs and RAG.

Week 1 introduces the fundamentals of LLMs and RAG. Week 2 is where the vector search magic begins. 

## What You'll Learn from Qdrant's Experts   
Qdrant’s team will guide you through both foundational and advanced concepts in vector and hybrid search:

Evgeniya (Jenny) Sukhodolskaya, Developer Advocate at Qdrant  
→ Learn how to run locally semantic similarity search with Qdrant and [FastEmbed](https://qdrant.tech/documentation/fastembed/) (Qdrant's optimized embedding solution) as well as gain visual understanding of vector search with Qdrant's [WebUI](https://qdrant.tech/documentation/web-ui/). 

Kacper Łukawski, Senior Developer Advocate at Qdrant  
→ Dive into [hybrid search](https://qdrant.tech/articles/hybrid-search/): combining lexical and vector search for better results. You’ll also explore multi-vector search, [reranking](https://qdrant.tech/documentation/advanced-tutorials/reranking-hybrid-search/), and [late interaction models](https://qdrant.tech/articles/late-interaction-models/).

## How to Join  
The course is 100% free and online, with all materials publicly available.

[Start the course today!](https://github.com/DataTalksClub/llm-zoomcamp).