Responsible Artificial Intelligence Practices

Overview

In this course, you will learn about responsible AI practices. First, you will be introduced to what responsible AI is.

You will learn how to define responsible AI, understand the challenges that responsible AI attempts to overcome, and explore the core dimensions of responsible AI.

Then, you will dive into some topics for developing responsible AI systems. You will be introduced to the services and tools that AWS offers to help you with responsible AI.

You will also learn about responsible AI considerations for selecting a model and preparing data for your AI systems.

Finally, you will learn about transparent and explainable models. You will gain a solid understanding of what it means for a model to be transparent and explainable.

You will also explore tradeoff considerations for transparent models and the principles of human-centered design for explainable AI.

• Course level:

  Fundamental

• Duration:

  1 hour

Activities

This course includes interactive elements, text instruction, illustrative graphics, and knowledge checks.

Course Objectives

In this course, you will learn how to do the following:

• Describe responsible AI
• Explain biases in AI models
• Identify the risk of generative AI
• Identify the core dimensions of responsible AI
• Describe services and tools AWS offers for responsible AI
• Explain responsible practices for selecting a model
• Describe responsible characteristics of responsible datasets
• Describe transparent and explainable models
• Identify responsible tradeoffs of AI models
• Explain the principles of human-centered design

Intended Audience

This course is intended for:

• Individuals interested in machine learning and artificial intelligence, independent of a specific job role

Prerequisites

Responsible AI Practices is part of a series that lays a foundation on artificial intelligence, machine learning, and generative AI. If you have not done so already, it is recommended that you complete these two courses:

• Fundamentals of Machine Learning and Artificial Intelligence
• Exploring Artificial Intelligence Use Cases and Applications

Course Outline

Section 1:

Introduction

• Introduction

Section 2:

Introduction to Responsible AI

• What is responsible AI
• Challenges of responsible AI
• Core dimensions of responsible AI
• Knowledge check

Section 3:

Developing Responsible AI Systems

• Amazon services and tools for responsible AI
• Responsible considerations for selecting a model
• Responsible preparation for datasets
• Knowledge check

Section 4:

Transparent and Explainable AI Models

• What are transparent and explainable models
• Responsible AI model tradeoffs
• Principles of human-centered design for explainable AI
• Knowledge checkpoint

Section 5:

Resources

• Links to AWS services

Keywords

• Gen AI
• Generative AI

Provider:

AWS Skill Builder

Categories:

Artificial Intelligence Courses, Machine Learning Courses, Ethics Courses, Data Privacy Courses

Subjects

united states