What You'll Learn
- Differentiate between predictive and generative AI and identify their appropriate business applications.
- Apply core ethical principles like fairness, accountability, transparency, and privacy in AI projects.
- Design and implement a Responsible AI control framework using real-world case studies and governance tools.
- Conduct bias detection, mitigation, and explainability analysis to ensure trustworthy AI systems.
- Build and operationalize an AI governance model with defined roles, risk tiers, and human oversight mechanisms.
Requirements
- Basic understanding of business or technology concepts (no coding required).
- Curiosity about how AI systems make decisions and impact society.
- An interest in data-driven innovation and organizational ethics.
- Access to a computer or device for viewing course content.
- No prior AI or programming experience needed — you’ll learn everything step-by-step.
Who This Course is For
- Business leaders and managers responsible for AI adoption or digital transformation.
- Data professionals and analysts seeking to integrate ethical frameworks into AI workflows.
- Compliance, risk, and governance professionals working on AI policy or responsible innovation.
- Educators and students exploring the foundations of ethical AI in business.
- Anyone who wants to ensure AI systems are built responsibly, transparently, and inclusively.
Your Instructor
Kavitha P
Working as Solution Architect in IBM
4.6 Instructor Rating
5 Reviews
3,337 Students
12 Courses
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