| File Name: | AI Ethics and Governance for Everyone 2025 |
| Content Source: | https://www.udemy.com/course/ai-ethics-and-governance-for-everyone-2025/?couponCode=LETSLEARNNOW |
| Genre / Category: | Other Tutorials |
| File Size : | 244.9 MB |
| Publisher: | Anup Techeazyai |
| Updated and Published: | July 8, 2025 |
Go from Theory to Practice. Learn to Build, Govern, and Lead Responsible AI with Real-World Frameworks and Tools.
In an era powered by AI, ethical literacy is a critical skill. This course provides a clear, practical path to understanding and implementing AI ethics. You’ll move beyond abstract concepts and learn to use globally recognized governance frameworks, test for bias, and navigate the complex regulatory landscape. By the end, you’ll have the confidence and tools to build, manage, and lead trustworthy AI initiatives.
What you’ll learn
- Implement Practical AI Governance using the official NIST AI Risk Management Framework.
- Detect and Mitigate Algorithmic Bias with an understanding of industry tools like Fairlearn and AI Fairness 360.
- Navigate the Global Regulatory Landscape, including the EU AI Act and the divergent approaches of the US and China.
- Master the Core Principles of Fairness, Accountability, and Transparency (FAT) in real-world projects.
- Analyze Frontier Ethical Challenges in Generative AI, Autonomous Systems, and the emerging field of Neurorights.
- Create “Model Cards” and other structured documentation for responsible AI development.
Who this course is for:
- AI/ML Developers, Data Scientists, and Engineers: Professionals who are building AI systems and want to learn how to implement ethics-by-design, mitigate bias, and use technical toolkits for explainability.
- Product Managers and Business Leaders: Individuals responsible for AI strategy, product roadmaps, and risk assessment who need to make informed decisions that align business goals with ethical standards.
- Compliance, Legal, and Policy Professionals: Specialists who navigate the complex web of global regulations, internal governance policies, and liability issues emerging in the AI space.
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