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Duration 14 hours
Course Outline
The Foundations of Gemini 3 Safety
- Exploring how Gemini 3 enhances safety and reliability
- Analyzing mechanisms for vulnerability reduction
- Surveying threat categories specific to AI systems
Governance Principles and Policy Alignment
- Aligning organizational policies with AI usage standards
- Configuring Gemini 3 for compliance in regulated industries
- Implementing governance workflows for ongoing oversight
Defending Against Prompt Injection
- Identifying various types of prompt-based attacks
- Constructing prompt architectures resistant to manipulation
- Testing and evaluating potential vulnerability surfaces
Responsible Data Management
- Handling sensitive or high-risk data effectively
- Safeguarding the ethical use of datasets
- Mitigating risks related to data leakage and confidentiality
Auditing and Monitoring AI Behavior
- Establishing pipelines for continuous behavior monitoring
- Detecting and analyzing anomalous outputs
- Maintaining audit trails to support compliance assurance
Risk Assessment and Scenario Planning
- Evaluating risks within AI-assisted operations
- Formulating effective mitigation strategies
- Simulating adverse scenarios to ensure organizational preparedness
Strategies for Secure Deployment
- Defining clear deployment boundaries
- Integrating Gemini 3 with secure infrastructure components
- Applying least-privilege architectural patterns
Organizational Readiness and Best Practices
- Developing cross-functional processes for AI safety
- Ensuring staff are prepared and capable of managing AI risks
- Planning long-term strategies for governance maturity
Summary and Recommended Next Steps
Requirements
- A solid grasp of cybersecurity fundamentals
- Hands-on experience with AI or machine learning-based systems
- Familiarity with governance or compliance workflows
Target Audience
- Security engineers
- Compliance teams
- AI ethics specialists
Testimonials (1)
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