INTERMEDIATE

Embeddings and Vector Search

Use embedding models and vector retrieval for semantic discovery. Part of the free AWS Bedrock Academy โ€” every lesson below is open to everyone, no signup required.

2 lessons150 XP~19 min total100% free

// LESSONS IN THIS MODULE

  1. 01Embedding Fundamentals9 min ยท 75 XP

    From Text to Vector Space Embeddings map text into dense vectors where semantic similarity is measurable as geometric distance. "Reset my password" an...

  2. 02Hybrid Retrieval Strategies10 min ยท 75 XP

    Dense + Keyword Works Better in Production Hybrid retrieval combines semantic vector search with lexical (keyword/BM25) matching. Dense vectors unders...

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Embeddings and Vector Search โ€” AWS Bedrock Academy Module | Free Lessons