landing_page/qdrant-landing/content/documentation/tutorials-search-engineering/_index.md

title, weight, is_empty, hideInSidebar, aliases, partition

title	weight	is_empty	hideInSidebar	aliases	partition
Search Engineering	32	true	true	how-to tutorials	qdrant

Search Engineering Tutorials

Master vector search modalities, reranking, and retrieval quality.

Tutorial	Objective	Stack	Time	Level
Hybrid Search with FastEmbed	Combine dense and sparse search for startups.	FastAPI	20m	Beginner
Neural Search Service	Deploy a search service for company descriptions.	FastAPI	30m	Beginner
Movie Recommendations	Collaborative filtering using sparse embeddings.	Python	45m	Intermediate
Advanced PDF Retrieval	PDF RAG using ColPali and embedding pooling.	Python	30m	Intermediate
Retrieval Quality Benchmarking	Measure quality and tune HNSW parameters.	Python	30m	Intermediate
Multivector Reranking	Use multivector representations for better ranking.	Python	30m	Intermediate
Hybrid Search Reranking	Implement late interaction and sparse reranking.	Python	40m	Intermediate
Semantic Code Search	Navigate codebases using vector similarity.	Python	45m	Intermediate
Static Embeddings Analysis	Evaluate the renaissance of static embeddings.	Python	20m	Intermediate