Generative AI Essentials on AWS
Field | Description / Template |
|---|---|
Purpose | To provide a foundational understanding of generative AI concepts and strategies, enabling professionals to identify viable use cases and plan AI projects that solve real-world business problems. |
Audience | Non-technical professionals and business-facing roles looking to bridge the gap between business needs and AI capabilities. |
Role | Business Analysts, IT Support, Marketing Professionals, Product/Project Managers, Line-of-Business Managers, and Sales Professionals. |
Domain | Generative AI / Business Strategy / Digital Transformation. |
Skill Level | Beginner |
Style | Conceptual and strategy-focused, providing practical insights into implementation planning and responsible AI usage. |
Duration | 1 Day |
Related Technologies | Generative AI, Machine Learning, Foundation Models |
Course Description
Generative AI Essentials on AWS covers the fundamental concepts, methods, and strategies for leveraging generative AI within a professional environment. You will gain a solid understanding of how generative AI addresses specific business needs through real-world use cases. The course provides practical insights into the underlying technologies and how they can be applied to solve complex problems. By the conclusion of the training, you will be equipped to explore project planning and lead discussions on the implementation of generative AI within your own organization.
Who is this course for
This course is designed for professionals in business and IT support roles who need to understand the "what" and "why" of generative AI. It is ideal for decision-makers and contributors who need to evaluate AI opportunities without necessarily writing code or managing infrastructure.
Course Objectives
Summarize generative AI concepts, methods, and overarching strategies.
Discuss the appropriate application of generative AI versus traditional machine learning.
Describe how to deploy and use generative AI technologies responsibly and safely.
Recognize different types of generative AI solutions through the lens of specific industry use cases.
Explain the steps required for implementation and project planning within an organizational framework.
Prerequisites
Skill Level: Fundamental.
Experience: No prior technical or AI experience is required. A basic understanding of cloud computing concepts is beneficial but not mandatory.
Course outline
Section 1: Introducing Generative AI
Generative AI explained
Foundation models
AWS generative AI services
Section 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
Section 3: Essentials of Prompt Engineering
Hands-on Lab: Optimizing Slogan Generation with Amazon Bedrock
Introduction to prompt engineering
Prompt design best practices
Advanced prompting strategies
Model settings and parameters
Section 4: Responsible AI Principles and Considerations
Hands-on Lab: Implementing Responsible AI Principles with Amazon Bedrock Guardrails
Introduction to responsible AI
Core dimensions of responsible AI
Generative AI considerations
Section 5: Security, Governance, and Compliance
Security overview
Adverse prompts
Generative AI security services
Governance
Compliance
Section 6: Implementing Generative AI Projects
Introduction AI Generative AI application
Define a use case
Select a foundational model
Improve performance
Evaluate results
Deploy the application
Amazon Q Business (guided demo)
Section 7: Integrating Generative AI into the Development Lifecycle
Hands-on Lab: Capstone - Creating a Project Plan with Generative AI
Introduction