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Amazon Web Services

Introduction to Responsible AI

Amazon Web Services and Amazon via AWS Skill Builder

Overview

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This course provides an overview of what responsible AI is and why it is important in the context of generative AI. Responsible AI refers to the development, deployment, and use of AI in an ethical, transparent, fair, and accountable manner. The course covers core dimensions of responsible AI; establishing best practices for fairness, explainability, privacy, robustness, governance, and transparency. This course also introduces services and tools to build AI responsibly on AWS.

  • Course level: Fundamental
  • Duration: 60-75min

Activities

This course includes presentations, practical examples and knowledge checks.

Course Objectives

In this course you will learn to:

  • Understand what responsible AI is and why it is important.
  • Review challenges that generative AI brings.
  • Define core dimensions of responsible AI.
  • Learn how to evaluate models for fairness and explainability.
  • Recognize best practices for designing responsible AI systems.
  • Identify services and tools to build AI responsibly on AWS.

Intended Audience

This course is intended for:

  • Practitioners looking to design and build responsible AI systems
  • Decision makers
  • Governance and compliance stakeholders

Prerequisites

We recommend that attendees of this course have:

  • Introduction to Generative AI – Art of the Possible (digital), or equivalent experience
  • No prior cloud computing or AWS experience required

Course Outline

Module 1: Generative AI overview

  • What is generative AI?
  • Common use cases for generative AI
  • Risks and challenges with adopting generative AI

Module 2: Introduction to responsible AI

  • Defining Responsible AI
  • What is responsible AI?
  • Responsible AI throughout the lifecycle
  • Responsible AI in practice

Module 3: Core dimensions of responsible AI

  • Fairness
  • Explainability
  • Privacy & security
  • Robustness
  • Governance
  • Transparency

Module 4: Services and tools to build AI responsibly on AWS

  • Model evaluation on Amazon Bedrock
  • Guardrails for Amazon Bedrock
  • Amazon SageMaker Clarify
  • Amazon SageMaker Model Monitor
  • ML governance with Amazon SageMaker
  • Amazon Augmented AI

Module 5: Knowledge Check and summary

Keywords

  • GenAI
  • Generative AI

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