Stalwart Learning’s “Data Privacy – Security & Ethics in GenAI” course is a focused, two-day program aimed at equipping professionals with the essential knowledge to navigate the complex landscape of data privacy, security, and ethical considerations in Generative AI. This course addresses the latest challenges in safeguarding sensitive data while leveraging AI capabilities, ensuring compliance with privacy regulations, and maintaining ethical standards. Through practical case studies and interactive discussions, participants will gain a comprehensive understanding of how to implement secure and responsible AI practices, making this course ideal for AI practitioners, data officers, and compliance professionals.
Duration
2 Days
Prerequisites
Basic understanding of data privacy laws and AI concepts
Familiarity with data security practices and compliance standards
No programming experience is required
Course Outline
Module 1
Introduction to Data Privacy in Generative AI
- Overview of data privacy concerns in AI
- Key regulations: GDPR, CCPA, and others
Data Security in Generative AI Systems
- Identifying vulnerabilities in GenAI systems
- Securing sensitive data used in AI models
Ethical Considerations in AI Development
- Understanding ethical implications of AI applications
- Case studies on ethical AI challenges
Interactive Workshop: Data Security Frameworks
- Hands-on session to implement basic security measures
Module 2
Compliance and Regulatory Best Practices
- Key compliance steps for AI data handling
- Navigating regulatory landscapes and updates
Bias and Fairness in Generative AI
- Identifying and mitigating bias in AI models
- Ensuring fairness and transparency in AI outcomes
Ethics in Action: Practical Guidelines for Responsible AI
- Building ethical guidelines for AI usage
- Ensuring accountability in AI-driven decisions
Case Study and Group Discussion: Implementing Ethical AI
Group discussion and Q&A on best practices
Analyzing a real-world scenario involving data privacy and ethics