Responsible AI: Ethics, Bias, Risk & Governance

About this course

Artificial Intelligence is transforming how organizations make decisions, automate processes, and deliver value. However, with this power comes responsibility. This course, Responsible AI: Ethics, Bias, Risk & Governance, is designed to help you understand not just how AI works, but how to use it responsibly in real-world environments.

In today’s rapidly evolving landscape, professionals are expected to understand AI ethics, bias in AI, data privacy, explainability, and governance frameworks. This course provides a structured, practical, and business-focused approach to mastering these essential areas without requiring any coding or technical background.

You will begin by building a strong foundation in how AI systems operate, including predictive, generative, and agentic AI. From there, you will explore how bias enters AI systems, how it impacts decision-making, and how it can be detected and mitigated using practical techniques. The course emphasizes real-world scenarios where biased AI systems can affect hiring, lending, healthcare, and other critical domains.

A significant focus is placed on data privacy and responsible data handling, including anonymization techniques, consent, and data protection principles. You will also learn how to make AI systems more transparent through explainability methods that help stakeholders understand how decisions are made.

As the course progresses, you will develop the ability to perform AI risk assessments, implement human-in-the-loop systems, and monitor AI performance after deployment. You will also explore AI governance frameworks, organizational responsibilities, and global regulatory trends such as risk-based AI compliance.

What makes this course different is its strong practical orientation. You will learn to detect bias in datasets, anonymizing data, explaining AI decisions, and building a simple governance framework. This course i

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