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Course Outline
Introduction to Privacy in AI Deployments for Government
- Privacy Challenges in AI Systems for Government
- Ollama’s Role in Privacy-Conscious Environments for Government
- Overview of Compliance Considerations (GDPR, HIPAA, etc.) for Government
Secure Containerization and Deployment for Government
- Hardening Docker and Kubernetes Environments for Government
- Network Security and Isolation Techniques for Government
- Secrets Management and Key Rotation for Government
On-Device and On-Prem Inference for Government
- Advantages of Local Inference for Privacy in Government Operations
- Edge Deployment Patterns for Government
- Balancing Performance with Compliance for Government
Differential Privacy and Data Protection for Government
- Principles of Differential Privacy for Government
- Applying Noise Mechanisms to AI Workflows for Government
- Data Minimization and Anonymization Strategies for Government
Logging, Monitoring, and Auditing for Government
- Secure Logging Practices for Government
- Audit Trails for Compliance in Government
- Real-Time Monitoring and Alerting for Government
Access Control and Policy Enforcement for Government
- Role-Based Access Control (RBAC) for Government
- Policy Enforcement with Open Policy Agent for Government
- Data Governance Frameworks for Government
Case Studies and Best Practices for Government
- Deploying Ollama in Regulated Industries for Government
- Balancing Usability and Privacy for Government
- Lessons Learned from Real-World Implementations for Government
Summary and Next Steps for Government
Requirements
- Knowledge of IT security principles for government
- Experience with containerization and deployment processes
- Familiarity with compliance frameworks such as GDPR or HIPAA
Audience
- Security engineers
- IT architects
- Privacy officers
- Compliance teams
14 Hours
