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Duration 14 hours
Course Outline
Foundations of Gemini 3 Safety
- Exploring how Gemini 3 enhances safety and reliability.
- Understanding mechanisms for reducing vulnerabilities.
- An overview of threat categories relevant to AI systems.
Governance Principles and Policy Alignment
- Aligning organizational policies with AI usage standards.
- Configuring Gemini 3 for operation in regulated environments.
- Establishing governance workflows for continuous oversight.
Defending Against Prompt Injection
- Identifying various types of prompt-based attacks.
- Constructing prompt structures that resist manipulation.
- Assessing and testing potential vulnerability surfaces.
Responsible Data Management
- Handling sensitive or high-risk data effectively.
- Promoting ethical usage of datasets.
- Mitigating risks related to data leakage and confidentiality.
Auditing and Monitoring AI Behavior
- Implementing pipelines for behavioral monitoring.
- Detecting anomalous outputs and deviations.
- Maintaining audit trails to ensure compliance.
Risk Assessment and Scenario Planning
- Evaluating risks associated with AI-assisted operations.
- Formulating effective mitigation strategies.
- Simulating adverse scenarios to enhance preparedness.
Secure Deployment Strategies
- Defining clear deployment boundaries.
- Integrating Gemini 3 with secure infrastructure components.
- Adopting least-privilege architectural patterns.
Organizational Readiness and Best Practices
- Developing cross-functional AI safety processes.
- Ensuring staff readiness and technical capability.
- Advancing long-term governance maturity.
Conclusion and Next Steps
Requirements
- A solid grasp of cybersecurity fundamentals.
- Practical experience with AI or machine learning-based systems.
- Working knowledge of governance or compliance workflows.
Target Audience
- Security engineers.
- Compliance teams.
- AI ethics specialists.
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