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Video course · 10 chapters · 336 min · certificate

Enterprise AI Engineering: Embeddings, RAG, and Multimodal Agents with AWS Bedrock and Nova

Enterprise AI engineering on AWS: embeddings in NLP and LLMs, byte-pair encoding, Amazon Titan text embeddings, multimodal LLMs, CLIP, BLIP-2, Amazon Nova, multimodal RAG with Bedrock and LangChain, and Bedrock agents with knowledge bases.

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What you'll learn

  • Explain embeddings and tokenisation
  • Use Amazon Titan embeddings
  • Understand multimodal models like CLIP and BLIP-2
  • Use Amazon Nova
  • Build multimodal RAG on Bedrock
  • Create Bedrock agents with knowledge bases

Chapters

10 chapters · 336:23
  1. 3:45 01Intro Members Introduction Course scope.
  2. 31:01 02Embeddings Members Embeddings in NLP and LLMs Representing meaning.
  3. 64:00 03Tokenisation Members Byte-pair encoding Subword tokens.
  4. 30:40 04Titan Members Amazon Titan text embeddings AWS embeddings.
  5. 16:58 05Multimodal Members Multimodal LLMs Beyond text.
  6. 21:56 06Vision-language Members CLIP Contrastive pre-training.
  7. 25:26 07Vision-language Members BLIP-2 Frozen encoders + LLM.
  8. 38:11 08Nova Members Amazon Nova AWS multimodal models.
  9. 45:24 09RAG Members Multimodal RAG Bedrock, Nova and LangChain.
  10. 59:02 10Agents Members Agents with knowledge bases Insurance use case.

Jobs this course suits

Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.

AI EngineersMachine Learning EngineersData ArchitectsSoftware ArchitectsCloud ArchitectsData ScientistsSoftware EngineersBackend DevelopersSoftware DevelopersSolutions Architects