This module introduces the course structure and objectives.

Course Introduction

This module provides an overview of Responsible AI, covering Google’s AI Principles and sub-topics of Responsible AI. Also, this provides actual case studies of Responsible AI in Google products.

AI & Responsibility

Google’s AI Principles

Responsible AI Practices

Case study: Google Flights

Quiz Question 1

Quiz Question 2

Quiz Question 3

Quiz Question 4

Introduction to Responsible AI

This module focuses on AI Fairness and Bias. It provides various techniques and tools to identify and mitigate biases through data and modeling.

Overview of Fairness and Bias

Identify Bias - TFDV Tool

Identify Bias - What-if Tool

Identify Bias - TFMA Tool

Mitigate Bias - Data Intervention

Mitigate Bias - Threshold Calibration

Mitigate Bias - Model Remediation

AI Fairness & Bias

This module provides a summary of the entire course by covering the most important concepts, tools, and technologies.

Course Summary

Reading

Course Resources

This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.

Responsible AI for Developers: Fairness & Bias

This course covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. 


Reading

Responsible AI for Developers: Fairness & Bias

Hands-on interactive exercise