Responsible AI: Applying AI Principles with Google Cloud

It covers defining fairness in ML systems, detecting and mitigating bias in datasets and models, making models interpretable, and applying Google's own AI principles. What makes it worthwhile is that it stays concrete: bias and fairness are easy to nod along to in the abstract, and this pushes toward actually detecting and addressing them in a real model.

It's principle-led and accessible, so it's a solid grounding for anyone who builds or governs AI, and the wrong course if you want deep technical fairness engineering or the legal and policy side. Audit it free on Coursera; a certificate needs a subscription (about $49/month) or Coursera Plus, with financial aid available. Responsible-AI practice only grows more important (as of 2026).

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.