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LinkedIn Learning

Building Applications Using Amazon Bedrock

via LinkedIn Learning

Overview

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Find out how you can use Amazon Bedrock to build applications for the most typical Generative AI use cases.

Syllabus

Introduction
  • Building Amazon Bedrock applications
  • What you should know
  • AWS setup
  • Set up AWS credentials
1. Key Concepts
  • Amazon Bedrock
  • LangChain
  • Streamlit
  • Retrieval-augmented generation (RAG)
  • Model overviews
2. Conversational Chatbot
  • Use case overview
  • Architecture review
  • Setting up your knowledge base
  • Writing the code: Knowledge base interaction
  • Demo: Knowledge base interaction
  • Part 1
    • Coding: Adding Streamlit integration
    • Part 2
      • Coding: Adding Streamlit integration
      • Demo: Streamlit UI
      3. Application Enhancements
      • Conversation history
      • Coding: Supporting conversation history
      • Demo: Chatbot conversation history
      • Introduction to Amazon Kendra
      • Setting up the Amazon Kendra index
      • Coding: Amazon Kendra integration
      • Setting permissions for Amazon Kendra
      • Demo: Amazon Kendra and Amazon Bedrock integration
      • Agents for Bedrock
      • Configuring the Amazon Bedrock agent
      • Reviewing project files
      • Testing the agent in the AWS console
      Conclusion
      • Cleanup for Amazon Bedrock
      • Continuing your application development with Amazon Bedrock

Taught by

Lee Assam

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