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Responsible AI: Applying AI Principles with Google Cloud

4.6(5,000)·80K enrolled
Beginner 8 hours English Course Certificate Certificate

About this course

This Google Cloud course covers responsible AI principles and practices: defining fairness in ML systems, detecting and mitigating bias in datasets and models, making models interpretable, and applying Google's seven AI principles.

Hands-on labs use Google's AI Explanations and What-If Tool, giving practitioners concrete skills for auditing AI fairness in production systems.

What you'll learn

Define and measure fairness in ML systems across different criteria
Identify and mitigate bias in training data and model predictions
Apply explainability techniques including SHAP and integrated gradients
Use Google's What-If Tool for fairness and performance analysis
Apply Google's responsible AI principles to real development decisions

This course includes

8h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
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Instructor

GC
Google Cloud Teaching Staff
Coursera instructor
80K+ learners10 courses4.6 instructor rating

Developed by Google Cloud's AI education team, drawing on Google's internal responsible AI practices and research from Google Brain.

Requirements

  • Basic ML knowledge; Python familiarity helpful for labs

Who this course is for

  • ML engineers and data scientists building production AI systems
  • Product managers responsible for ethical AI governance
  • Teams building AI products in regulated industries

About this provider

CO
Coursera
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Frequently asked questions

The tools are Google Cloud, but fairness concepts and frameworks apply universally across any ML stack.
Yes — the course aligns with EU AI Act requirements and enterprise AI governance frameworks.
Paid
Free to audit, paid certificate
Enroll now