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Duration 14 hours
Course Outline
Foundations of Gemini 3 Safety
- How Gemini 3 enhances safety and reliability
- Understanding mechanisms for reducing vulnerabilities
- Overview of threat categories specific to AI systems
Governance Principles and Policy Alignment
- Aligning organizational policies with AI usage
- Configuring Gemini 3 for regulated environments
- Implementing governance workflows for continuous oversight
Prompt Injection Defense
- Identifying types of prompt-based attacks
- Constructing resistant prompt structures
- Evaluating and testing vulnerability surfaces
Responsible Data Handling
- Managing sensitive or high-risk data
- Ensuring the ethical use of datasets
- Mitigating risks related to data leakage and confidentiality
Auditing and Monitoring AI Behavior
- Establishing behavior monitoring pipelines
- Detecting anomalous outputs
- Maintaining audit trails for compliance assurance
Risk Assessment and Scenario Planning
- Evaluating risks in AI-assisted operations
- Developing mitigation strategies
- Simulating adverse scenarios to ensure preparedness
Secure Deployment Strategies
- Defining deployment boundaries
- Integrating Gemini 3 with secure infrastructure
- Applying least-privilege architectural patterns
Organizational Readiness and Best Practices
- Developing cross-functional AI safety processes
- Ensuring staff readiness and capability
- Long-term strategies for governance maturity
Summary and Next Steps
Requirements
- A solid grasp of cybersecurity fundamentals
- Experience working with AI or ML-based systems
- Knowledge of governance or compliance workflows
Target Audience
- Security engineers
- Compliance teams
- AI ethics professionals
Testimonials (1)
Flow , vibe and topic on presentation
