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Duration 14 hours
Course Outline
Foundations of Gemini 3 Safety
- How Gemini 3 enhances overall safety and reliability
- Comprehending mechanisms for reducing vulnerabilities
- A broad overview of threat categories affecting AI systems
Governance Principles and Policy Alignment
- Aligning organizational policies with AI usage standards
- Configuring Gemini 3 for compliance within regulated sectors
- Implementing governance workflows for continuous oversight
Prompt Injection Defense
- Identifying various types of prompt-based attacks
- Constructing prompt structures that resist manipulation
- Assessing and testing potential vulnerability surfaces
Responsible Data Handling
- Managing sensitive or high-risk data effectively
- Ensuring the ethical utilization of datasets
- Mitigating risks associated with data leakage and confidentiality
Auditing and Monitoring AI Behavior
- Establishing pipelines for behavior monitoring
- Detecting anomalous AI outputs
- Maintaining audit trails to ensure compliance
Risk Assessment and Scenario Planning
- Evaluating risks associated with AI-assisted operations
- Developing effective mitigation strategies
- Simulating adverse scenarios to enhance preparedness
Secure Deployment Strategies
- Defining clear deployment boundaries
- Integrating Gemini 3 with secure infrastructure
- Utilizing least-privilege architectural patterns
Organizational Readiness and Best Practices
- Developing cross-functional AI safety processes
- Ensuring staff are prepared and capable
- Strategies for long-term governance maturity
Summary and Next Steps
Requirements
- A solid grasp of cybersecurity fundamentals
- Practical experience with AI or ML-based systems
- Aquaintance with governance and compliance workflows
Target Audience
- Security Engineers
- Compliance Teams
- AI Ethics Professionals
Testimonials (1)
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