Course :: Generative AI and RAG (Retrieval-Augmented Generation) with Amazon Bedrock

• 2 days

Outline

• Introduction to Generative AI
  • Basic of Generative AI
  • Large Language Model (LLM)
• Basic of Prompt engineering
  • Structured prompt
  • Zero-shot prompt
  • Chain of Thought (COT)
  • ReAct
  • Workshop with prompts
• Introduction to RAG (Retrieval-Augmented Generation)
  • RAG architecture
    • Retriever: Types of retrieval systems (vector stores, BM25).
    • Augmenter: Combining retrieved data with generative models.
    • Generator: Generative AI models supported by Bedrock.
  • Benefits and use cases
  • RAG pipeline or processes
  • Workshop with RAG
    • Chunking
    • Embedding
    • Re-ranking
• Understanding Amazon Bedrock
  • Overview of Amazon Bedrock and services.
  • Supported foundational models and their use cases
  • Integration of RAG with Amazon Bedrock: High-level architecture
• RAG Workshop by use cases
  • Knowledge-based management
  • Customer management
  • Integrating RAG with applications like chatbots and search