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Duration 14 hours
Course Outline
Foundations of Gemini 3 Safety
- How Gemini 3 enhances safety and reliability
- Comprehending mechanisms for vulnerability reduction
- Overview of threat categories relevant to AI systems
Governance Principles and Policy Alignment
- Aligning organizational policies with AI usage
- Configuring Gemini 3 for regulated environments
- Establishing governance workflows for ongoing oversight
Defending Against Prompt Injection
- Identifying various types of prompt-based attacks
- Constructing prompt structures resistant to manipulation
- Assessing and testing for vulnerability surfaces
Responsible Data Management
- Handling sensitive or high-risk data effectively
- Ensuring ethical usage of datasets
- Mitigating risks related to data leakage and confidentiality
Auditing and Monitoring AI Conduct
- Implementing pipelines for behavioral monitoring
- Detecting anomalous outputs
- Maintaining audit trails for compliance verification
Risk Assessment and Scenario Planning
- Evaluating risks in AI-assisted operations
- Formulating 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 competency and readiness
- Advancing long-term governance maturity
Summary and Next Steps
Requirements
- A solid grasp of cybersecurity fundamentals
- Hands-on experience with AI or ML-based systems
- Familiarity with governance or compliance workflows
Target Audience
- Security engineers
- Compliance teams
- AI ethics specialists
Testimonials (1)
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