Responsible AI for Everyone

Edureka introduces responsible AI through the way systems make decisions and the risks that arise across their lifecycle. Fairness auditing, oversight and documentation connect the principles with operational controls. It suits learners who need a broad overview of trustworthy-system review without an advanced technical background.

What you will learn

• Identify AI risks and affected groups.
• Compare fairness and oversight considerations.
• Use documentation to explain system limitations.

Who this suits

AI practitioners, business and governance learners; basic AI or machine-learning understanding helps, while advanced technical knowledge is not required.

Before you enroll

Compare dated course examples with current provider documentation and the context of the proposed system. A framework is a starting point for review, not proof that a system is safe or compliant. Use synthetic examples and document assumptions, affected groups and unresolved questions.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Provider access terms can change; review them before paying.

Put it into practice

Draft a model card for a fictional system and make its intended use, data limitations, evaluation approach and human-review needs explicit.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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