Building AI Applications with AWS Bedrock
This one-day course provides developers with the knowledge and skills to integrate AI capabilities into their applications using AWS Bedrock. The course covers the fundamentals of AWS Bedrock, its features, and practical implementation strategies.
Prerequisites
- Basic understanding of AI and machine learning concepts
- Familiarity with AWS services
Contents
Introduction to AWS Bedrock
- Overview of AWS Bedrock
- Key features and benefits
- Understanding the AI capabilities of AWS Bedrock
Setting Up AWS Bedrock
- Creating and configuring an AWS Bedrock environment
- Integrating AWS Bedrock with other AWS services
Building AI Applications
- Using foundation models (e.g., Claude, Titan, Jurassic, Mistral) through the Bedrock API
- Deploying AI models in applications
- Best practices for AI model management
Prompt Engineering and Use Cases
- Best practices for writing prompts
- Understanding input/output tokens, latency, and cost trade-offs
- Example use cases: summarization, Q&A, code generation, etc.
Security, Access Control, and Cost Management
- Managing Bedrock access via IAM
- Monitoring usage and controlling costs
Hands-On Lab
- Building a sample AI application with AWS Bedrock
- Troubleshooting common issues
- Optimizing AI model performance
