Generative AI Essentials on AWS (GAIE)

Course Content

Module 1: Introducing Generative AI

• Generative AI explained
• Foundation models
• AWS generative AI services
• Demo: Generative AI solution

Module 2: Exploring Generative AI Use Cases

• Identify suitable use cases
• Generative AI applications and use cases
• Explore generative AI use case scenarios
• Use case for class

Module 3: Essentials of Prompt Engineering

• Introduction to prompt engineering
• Prompt design best practices
• Advanced prompting strategies
• Model settings and parameters
• Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock

Module 4: Responsible AI Principles and Considerations

• Introduction to responsible AI
• Core dimensions of responsible AI
• Generative AI considerations
• Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails

Module 5: Security, Governance, and Compliance

• Security overview
• Adverse prompts
• Generative AI security services
• Governance
• Compliance

Module 6: Implementing Generative AI Projects

• Introduction – Generative AI application
• Define a use case
• Select a foundational model
• Improve performance
• Evaluate results
• Deploy the application
• Demo: Amazon Q Business

Module 7: Integrating Generative AI into the Development Lifecycle

• Introduction
• Hands-on Lab: Capstone – Creating a Project Plan with Generative AI

Module 8: Course Wrap-up

• Next steps and additional resources
• Course summary

Prerequisites

None

Who Should Attend

This course is intended for those with limited prior knowledge of generative AI:

• Business analysts
• IT supports
• Marketing professionals
• Product or project managers
• Line-of-business or IT managers
• Sales professionals