- Introduction to Autonomous AI Agents
Overview of AI agent systems
Current use cases and applications
- Understanding Data Privacy in AI
Definition and importance of data privacy
Regulatory frameworks and compliance (e.g., GDPR, CCPA)
- Identifying Vulnerabilities in Autonomous AI Systems
Types of vulnerabilities
Case studies of notable breaches
- Adversarial Attacks on AI Agents
Nature and types of adversarial attacks
Techniques for detecting and mitigating attacks
- Prompt Injection Attacks
Concept and execution of prompt injection
Real-world examples and implications
- Defense Mechanisms in AI
Security best practices for AI systems
Designing robust defense architectures
- Building Resilient AI Deployments
Strategies for ongoing monitoring and updates
Balancing performance with security
- Emerging Threats and Future Challenges
Upcoming trends in AI security threats
Preparing for future adversities
- Hands-On Session: Implementing AI Security Measures
Practical exercises on securing AI systems
Group activities and case studies analysis
- Conclusion and Recommendations
Summarizing key learnings
Best practices for future-proof AI security planning
- Assessment and Certification
Final project or exam
Criteria for course completion and certification
- Resources and Further Reading
Recommended books, papers, and online resources
Community and professional network engagement opportunities