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Duration 14 hours
Course Outline
Core Concepts of Gemini 3 Safety
- Enhancements in safety and reliability within Gemini 3
- Mechanisms for reducing system vulnerabilities
- Classification of threat vectors in AI systems
Governance Standards and Policy Integration
- Aligning AI usage with organizational policies
- Configuring Gemini 3 for regulated sectors
- Workflows for ongoing governance oversight
Defending Against Prompt Injection
- Analysis of prompt-based attack methods
- Constructing prompt structures that resist manipulation
- Testing and assessing potential vulnerability points
Ethical Data Management
- Handling of sensitive and high-risk data
- Promoting ethical use of datasets
- Preventing data leakage and protecting confidentiality
Monitoring and Auditing AI Actions
- Establishing pipelines for behavioral monitoring
- Detection of irregular or anomalous outputs
- Maintaining audit logs for compliance verification
Risk Evaluation and Contingency Planning
- Evaluating risks in AI-supported operations
- Formulating risk mitigation strategies
- Role-playing adverse scenarios to ensure preparedness
Secure Implementation Tactics
- Defining deployment limits and boundaries
- Integrating Gemini 3 into secure infrastructure
- Applying least-privilege design principles
Organizational Preparedness and Industry Standards
- Developing cross-departmental AI safety processes
- Ensuring workforce competence and readiness
- Strategies for long-term governance maturity
Key Takeaways and Future Actions
Requirements
- Working knowledge of cybersecurity basics
- Background experience with AI or machine learning systems
- Understanding of governance and compliance procedures
Intended Participants
- Security engineers
- Compliance specialists
- AI ethics professionals
Testimonials (1)
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