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

title, weight, is_empty, aliases, partition

title	weight	is_empty	aliases	partition
Search Engineering	18	false	how-to tutorials	qdrant

Search Engineering Tutorials

Master vector search modalities, reranking, and retrieval quality.

Tutorial	Objective	Stack	Time	Level
Semantic Search Intro	Deploy a search service for company descriptions.	FastAPI	30m	Beginner
Hybrid Search with FastEmbed	Combine dense and sparse search.	FastAPI	20m	Beginner
Collaborative Filtering	Collaborative filtering using sparse embeddings.	Python	45m	Intermediate
Multivector Document Retrieval	PDF RAG using ColPali and embedding pooling.	Python	30m	Intermediate
Retrieval Quality Evaluation	Measure quality and tune HNSW parameters.	Python	30m	Intermediate
Hybrid Search with Reranking	Implement late interaction and sparse reranking.	Python	40m	Intermediate
Semantic Search for Code	Navigate codebases using vector similarity.	Python	45m	Intermediate
Multivectors and Late Interaction	Effective use of multivector representations.	Python	30m	Intermediate
Static Embeddings	Evaluate the utility of static embeddings.	Python	20m	Intermediate