### Search Engineering Tutorials
*Master vector search modalities, reranking, and retrieval quality.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Relevance Feedback](https://qdrant.tech/documentation/tutorials-search-engineering/using-relevance-feedback/index.md) | Relevance Feedback Retrieval in Qdrant | Python | 30m | Intermediate |
| [Collaborative Filtering](https://qdrant.tech/documentation/tutorials-search-engineering/collaborative-filtering/index.md) | Collaborative filtering using sparse embeddings. | Python | 45m | Intermediate |
| [Multivector Document Retrieval](https://qdrant.tech/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/index.md) | PDF RAG using ColPali and embedding pooling. | Python | 30m | Intermediate |
| [Measuring ANN Recall](https://qdrant.tech/documentation/tutorials-search-engineering/ann-recall/index.md) | Measure ANN recall with the Web UI and tune HNSW parameters. | Web UI | 15m | Beginner |
| [Multivectors and Late Interaction](https://qdrant.tech/documentation/tutorials-search-engineering/using-multivector-representations/index.md) | Effective use of multivector representations. | Python | 30m | Intermediate |
| [Multi-Representation Search](https://qdrant.tech/documentation/tutorials-search-engineering/multi-representation-search/index.md) | Fuse title, summary, chunk, and tag vectors with named vectors and the Query API. | Python | 45m | Intermediate |
| [Static Embeddings](https://qdrant.tech/documentation/tutorials-search-engineering/static-embeddings/index.md) | Evaluate the utility of static embeddings. | Python | 20m | Intermediate |
| [Branch-Aware Search](https://qdrant.tech/documentation/tutorials-search-engineering/branch-aware-search/index.md) | Scope search to a branch's live view in a versioned corpus, inherited from its ancestors. | Python | 25m | Intermediate |