Get in Touch
 Duration 14 hours

Course Outline

Core Concepts of Gemini 3 Safety

  • Enhancements in Gemini 3's safety and reliability standards
  • Mechanisms for reducing vulnerability exposure
  • Categorization of threats specific to AI systems

Governance Standards and Policy Integration

  • Aligning corporate policies with AI application usage
  • Setup procedures for Gemini 3 in regulated sectors
  • Workflows for sustained governance oversight

Defending Against Prompt Injection

  • Classification of prompt-based attack vectors
  • Constructing prompt architectures with built-in resistance
  • Testing and assessing potential vulnerability areas

Ethical Data Management

  • Handling of sensitive or high-stakes data
  • Promoting the ethical use of datasets
  • Preventing data leakage and safeguarding confidentiality

Monitoring and Auditing AI Performance

  • Implementation of behavior monitoring pipelines
  • Detection of irregular or anomalous outputs
  • Maintaining audit trails for compliance verification

Risk Evaluation and Scenario Modeling

  • Identifying risks in AI-assisted operational workflows
  • Formulating effective mitigation strategies
  • Simulating adverse conditions to test preparedness

Strategies for Secure Deployment

  • Defining deployment boundaries and limitations
  • Integrating Gemini 3 within secure infrastructure ecosystems
  • Adopting least-privilege architectural designs

Organizational Preparedness and Best Practices

  • Developing cross-departmental AI safety processes
  • Ensuring employee competence and readiness
  • Planning for long-term governance maturity

Conclusion and Future Actions

Requirements

  • Working knowledge of cybersecurity basics
  • Practical experience with AI or machine learning systems
  • Acquaintance with governance or compliance processes

Target Audience

  • Security Engineers
  • Compliance Teams
  • AI Ethics Specialists

Number of participants


Price per participant

Testimonials (1)

Upcoming Courses

Related Categories