AWS Certified AI Practitioner
Tokens, Chunking, and Embeddings
Follow a document from raw text to a searchable vector index: how text becomes tokens, why long documents get split into chunks, and how embeddings turn meaning into numbers you can compare.
Beginner 20 minutes 4 Learning Objectives
- Define a token and explain why a token is not the same as a word
- Explain why documents are chunked and compare the chunking strategies Amazon Bedrock supports
- Describe what an embedding is and how vector similarity finds related content
- Trace a document through the chunk, embed, and index pipeline that powers retrieval