5 modules(s) & 20 lesson(s)

• Module 1 - Understanding Ethical Challenges in Generative AI

  • 1 - Understanding Ethical Challenges in Generative AI - Introduction
  • 2 - Exploring Bias in Generative AI
  • 3 - Privacy Concerns in Generative AI
  • 4 - Accountability in Generative AI
  • 5 - Case Studies on Ethical Challenges
• Module 2 - Bias Mitigation Strategies in Generative AI

  • 1 - Understanding Bias Mitigation
  • 2 - Data Preprocessing Techniques
  • 3 - Algorithmic Fairness
  • 4 - Model Evaluation for Bias
  • 5 - Ethical Considerations in Bias Mitigation
• Module 3 - Preserving Privacy in Generative AI Systems

  • 1 - Privacy Preservation Fundamentals
  • 2 - Differential Privacy
  • 3 - Privacy-Enhancing Technologies
  • 4 - Privacy Regulations and Compliance
  • 5 - Privacy Impact Assessments
• Module 4 - Establishing Accountability Frameworks for Generative AI

  • 1 - Understanding Accountability in AI
  • 2 - Stakeholder Engagement
  • 3 - Transparency and Explainability
  • 4 - Auditing and Monitoring
  • 5 - Ethical Guidelines and Best Practices
• Module 5 - Completion