Learning Amazon Bedrock
1h 53mIntermediate2024-03-19
Authors

Lee Assam
Electrical and Software Engineer, University Instructor
Course details
In this course, principal cloud technologist Lee Assam introduces you to Amazon Bedrock and gives a foundational understanding of Generative AI and how foundation models (FMs) can be used to solve problems like text summarization, semantic/conversational search, and content generation. Using libraries like Python boto3, LangChain, and Streamlit, you will find out how to build Generative AI applications that leverage Foundational Large Language Models (LLMs) using APIs without managing infrastructure. Explore the pre-built FMs available in Amazon Bedrock and the features that Amazon Bedrock provides. Plus, practice what you learn as you build a basic Gen AI application using Amazon Bedrock to demonstrate its capabilities.
Skills covered
Amazon BedrockMachine LearningAmazonGenerative AIArtificial Intelligence (AI)Learning
Concepts
0. Introduction
- 01 - Learning Amazon Bedrock overview
- 02 - What you should know
- 03 - AWS setup
- 04 - Set up AWS credentials
1. Amazon Bedrock Introduction
- 05 - What is generative AI
- 06 - What is Amazon Bedrock
- 07 - Models in Amazon Bedrock
- 08 - Using Playgrounds for Amazon Bedrock
- 09 - Challenge - Image generation
- 10 - Solution - Image generation
2. Amazon Bedrock API Integration
- 11 - Amazon Bedrock API documentation
- 12 - Python Boto3 Amazon Bedrock support
- 13 - Invoking Amazon Bedrock APIs
- 14 - Introduction to LangChain
- 15 - Simple LangChain workflow
- 16 - Challenge - Language transalation
- 17 - Solution - Language translation
3. Building a GenAI Application
- 18 - What is RAG architecture
- 19 - Amazon Bedrock use case
- 20 - RAG application approach
- 21 - Coding the solution
- 22 - Running the solution
- 23 - Adding Streamlit integration
- 24 - Running the completed application
Conclusion
- 25 - Cleanup for Amazon Bedrock
- 26 - Amazon Bedrock application enhancements
- 27 - Continuing your Amazon Bedrock journey
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