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Duration 14 hours
Course Outline
Foundations of Gemini 3 Safety
- Ways Gemini 3 enhances safety and reliability
- Understanding mechanisms for vulnerability reduction
- An 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
- Establishing governance workflows for continuous oversight
Prompt Injection Defense
- Identifying types of prompt-based attacks
- Constructing prompt structures that resist manipulation
- Evaluating and testing vulnerability surfaces
Responsible Data Handling
- Managing sensitive or high-risk data
- Ensuring ethical usage of datasets
- Mitigating risks related to data leakage and confidentiality
Auditing and Monitoring AI Behavior
- Setting up pipelines for behavior monitoring
- Detecting anomalous outputs
- Creating audit trails to ensure compliance
Risk Assessment and Scenario Planning
- Assessing risks in AI-assisted operations
- Developing effective mitigation strategies
- Simulating adverse scenarios to improve preparedness
Secure Deployment Strategies
- Defining deployment boundaries
- Integrating Gemini 3 with secure infrastructure
- Applying least-privilege architectural patterns
Organizational Readiness and Best Practices
- Building cross-functional processes for AI safety
- Ensuring staff readiness and capability
- Developing long-term strategies for governance maturity
Summary and Next Steps
Requirements
- A solid grasp of cybersecurity fundamentals
- Practical experience with AI or ML-based systems
- Familiarity with governance or compliance workflows
Target Audience
- Security engineers
- Compliance teams
- AI ethics professionals
Testimonials (1)
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