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Duration 14 hours
Course Outline
Foundations of Gemini 3 Safety
- Examining how Gemini 3 enhances safety and reliability
- Comprehending vulnerability reduction mechanisms
- Surveying key threat categories affecting AI systems
Governance Principles and Policy Alignment
- Aligning organizational policies with AI utilization
- Configuring Gemini 3 for regulated environments
- Establishing governance workflows for continuous oversight
Prompt Injection Defense
- Identifying various types of prompt-based attacks
- Constructing resistant prompt architectures
- Assessing and testing vulnerability surfaces
Responsible Data Handling
- Managing sensitive or high-risk data assets
- Guaranteeing ethical usage of datasets
- Mitigating risks associated with data leakage and confidentiality
Auditing and Monitoring AI Behavior
- Implementing behavior monitoring pipelines
- Detecting anomalous outputs
- Maintaining audit trails for compliance assurance
Risk Assessment and Scenario Planning
- Evaluating risks in AI-assisted operations
- Formulating mitigation strategies
- Simulating adverse scenarios to enhance 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 readiness and capability
- Advancing long-term governance maturity
Summary and Next Steps
Requirements
- A foundational understanding of cybersecurity principles
- Practical experience with AI or ML-based systems
- Knowledge of governance or compliance workflows
Intended Audience
- Security engineers
- Compliance teams
- AI ethics professionals
Testimonials (1)
Flow , vibe and topic on presentation
