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AWS Authorized Training Course - AI Essentials on AWS

Course Summary

In this course, you will learn about the fundamental concepts, methods, and strategies for using generative AI. You will gain a solid understanding of use cases where generative AI can provide solutions and address business needs. Additionally, you will learn about practical insights into technologies related
to generative AI and how you can use those technologies to solve real-world problems. By the end of the course, you will explore project planning and how to discuss implementation of generative AI in your organization.

Prerequisites
We recommend that attendees of this course have:
• None

THIS COURSE IS NOT ELIGIBLE FOR TRAINING BUNDLES

Purpose
Gain practical insights into technologies used for generative AI
Audience
Anyone interested in advancing their understanding of Generative AI fundamentals
Role
Business analyst | IT support | Marketing professional | Product or project manager | Line-of-business or IT manager | Sales professional
Skill level
Fundamental
Style
Lecture | Hands-on Activities | Labs
Duration
1 day
Related technologies
AI/ML | AWS Cloud

 

Learning objectives
  • Summarize generative AI concepts, methods, and strategies
  • Discuss the appropriate use of generative AI and machine learning and their technologies
  • Describe how to use generative AI responsibly and safely
  • Recognize the types of generative AI solutions with specific use cases
  • Explain implementation and project planning of generative AI to your organization

What you'll learn:

In this Generative AI Essentials on AWS course, you'll learn:

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

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