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План на курса
Introduction to Privacy in AI Deployments
- Privacy challenges in AI systems
- Ollama’s role in privacy-conscious environments
- Overview of compliance considerations (GDPR, HIPAA, etc.)
Secure Containerization and Deployment
- Hardening Docker and Kubernetes environments
- Network security and isolation techniques
- Secrets management and key rotation
On-Device and On-Prem Inference
- Advantages of local inference for privacy
- Edge deployment patterns
- Balancing performance with compliance
Differential Privacy and Data Protection
- Principles of differential privacy
- Applying noise mechanisms to AI workflows
- Data minimization and anonymization strategies
Logging, Monitoring, and Auditing
- Secure logging practices
- Audit trails for compliance
- Real-time monitoring and alerting
Access Control and Policy Enforcement
- Role-based access control (RBAC)
- Policy enforcement with Open Policy Agent
- Data governance frameworks
Case Studies and Best Practices
- Deploying Ollama in regulated industries
- Balancing usability and privacy
- Lessons learned from real-world implementations
Summary and Next Steps
Изисквания
- Understanding of IT security principles
- Experience with containerization and deployment
- Familiarity with compliance frameworks such as GDPR or HIPAA
Audience
- Security engineers
- IT architects
- Privacy officers
- Compliance teams
14 часа
