Generative AI Essentials on AWS

This one-day ILT course provides a solid foundation in generative AI, covering the key concepts, use cases, and AWS services. It will be instrumental in large scale foundational enablement of target audience including mostly non-tech roles – who have little prior generative AI knowledge, are using, will use, or make decisions to use AI technologies but do not necessarily build AI solutions on AWS. Roles include but not limited to: Business analyst, IT support, Marketing professional, Product or project manager, Line-of-business or IT manager, Sales professional, etc.

On Completion of this course you will:

• Understand generative AI concepts, methods, and strategies in general and on AWS
• Understand the appropriate use of AI/ML and generative AI technologies
• Use generative AI technologies responsibly and safely
• Determine the correct types of generative AI technologies to apply to specific use cases
• Identify how to implement generative AI in your organization/ plan a Generative AI Project

This course will introduce the following AWS GenAI technologies:

• Amazon SageMaker
• Amazon Bedrock
• Amazon Q
• PartyRock

Target Audience

Business professionals and non-technical staff who require an appreciation of teh concepts and capabilties of the primary AWS GenAI tools

Module 1: Introducing to Generative AI

• GenAI Explained
• Foundation Models
• AWS Generative AI services

Module 2: Exploring Use Cases for Generative AI

• Identify suitable use cases
• GenAI Applications and use cases
• Generative AI use case: Activitiy
• Use Case for class

Module 3: Essentials of Prompt Engineering

• Introduction to prompt engineering
• Prompt design best practice
• Advanced Prompt strategies
• Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock and Claude Sonnet

Module 4: Responsible AI Principals and Considerations

• Intro to responsible AI
• Core Dimensions of responsible AI
• Implementing responsible AI
• GenAI considerations
• Hands-on Lab: Securing AI with Amazon Bedrock Guardrails

Module 5: Security, Governance, and Compliance

• Security Overview
• Adverse Prompts
• AWS security services
• Governance
• Compliance

Module 6: Implementing Generative AI Projects

• Introduction - Generative AI application Lifecycle
• Define a use case
• Select a foundation model
• improve performance
• Evaluate results
• Deploy the application

Module 7: Integrating Generative AI into the Development Lifecycle

• Amazon Q demo
• Hands-on Lab: Capstone: Creating a Project Plan with Generative AI

Module 8: Course Wrap-up