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Duration 14 hours
Course Outline
Foundations of Gemini 3 Safety
- How Gemini 3 enhances safety and reliability.
- Understanding mechanisms for vulnerability reduction.
- An overview of threat categories affecting 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 various types of prompt-based attacks.
- Constructing resistant prompt structures.
- Assessing and testing potential vulnerability surfaces.
Responsible Data Handling
- Managing sensitive or high-risk data effectively.
- Ensuring the ethical usage 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.
- Designing effective mitigation strategies.
- Simulating adverse scenarios to enhance preparedness.
Secure Deployment Strategies
- Defining 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 readiness and competency.
- Implementing long-term governance maturity strategies.
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.
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