Enterprise AI Tutorial – Embeddings, RAG, and Multimodal Agents Using Amazon Nova and Bedrock

Learn all about Embeddings, RAG, Multimodal Models, and Agents with Amazon Nova. This course covers AI engineering, covering a ton of technologies from Amazon Tian Text Embeddings to LangChain integration with Amazon Bedrock.

You'll build an end-to-end application utilizing Amazon Bedrock Agents and Knowledge Bases. This course demonstrates practical applications of these technologies, such as automating and optimizing the insurance claim process with AI.

You'll learn how to leverage Bedrock-powered agents to assist in tasks like claim creation, document management, and data retrieval, significantly enhancing efficiency and decision-making capabilities in customer service operations.

💻 GitHub: https://github.com/debnsuma/fcc-ai-engineering-aws

🏗️ Amazon provided a grant to make this course possible.

⭐️ Contents ⭐️
⌨️ (0:00:00) Introduction
⌨️ (0:03:45) Embeddings in NLP and LLMs
⌨️ (0:34:46) Byte-Pair Encoding (BPE)
⌨️ (1:38:46) Amazon Tian Text Embeddings
⌨️ (2:09:26) Multimodal LLMs
⌨️ (2:26:24) Contrastive Language-Image Pre-training (CLIP)
⌨️ (2:48:20) Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models (BLIP-2)
⌨️ (3:13:46) Amazon Nova Multimodal Model
⌨️ (3:51:57) Multimodal RAG
⌨️ (4:37:21) Agents with Knowledge Bases
⌨️ (5:36:14) Resources

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