Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to Privacy in AI Deployments
- Privacy challenges within AI systems
- Ollama’s function in privacy-conscious environments
- Overview of key compliance considerations (e.g., GDPR, HIPAA)
Secure Containerization and Deployment
- Strengthening Docker and Kubernetes environments
- Network security and isolation methods
- Management of secrets and key rotation
On-Device and On-Prem Inference
- Privacy benefits of local inference
- Edge deployment strategies
- Striking a balance between performance and compliance
Differential Privacy and Data Protection
- Core principles of differential privacy
- Integrating noise mechanisms into AI workflows
- Strategies for data minimization and anonymization
Logging, Monitoring, and Auditing
- Best practices for secure logging
- Creating audit trails for compliance purposes
- Real-time monitoring and alerting systems
Access Control and Policy Enforcement
- Role-based access control (RBAC)
- Implementing policy enforcement using Open Policy Agent
- Structuring data governance frameworks
Case Studies and Best Practices
- Deploying Ollama in highly regulated industries
- Navigating the balance between usability and privacy
- Key insights from real-world implementations
Summary and Next Steps
Requirements
- A solid grasp of IT security principles
- Practical experience with containerization and deployment processes
- Knowledge of compliance frameworks such as GDPR or HIPAA
Audience
- Security engineers
- IT architects
- Privacy officers
- Compliance teams
