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Duration 14 hours
Course Outline
Introduction to Responsible AI with Mistral
- Core principles of responsible AI
- Mistral’s enterprise features and development roadmap
- Compliance drivers and international regulatory landscape
Privacy and Data Protection
- Methods for anonymisation and pseudonymisation
- Encryption at rest and during transmission
- Managing data access and mitigating risk
Data Residency Strategies
- Regional hosting options
- Comparison of on-premises versus cloud deployments
- Hybrid residency models
Enterprise Controls and Integrations
- Role-based access control (RBAC)
- Single sign-on (SSO) and identity management
- Integration with existing enterprise IT systems
Auditability and Governance
- Configuring audit logs and monitoring solutions
- Governance playbooks for AI systems
- Incident response and escalation procedures
Vendor Options and Deployment Models
- Comparison of Mistral self-hosting and managed services
- Evaluating vendor compliance assurances
- Balancing cost, performance, and regulatory considerations
Case Studies and Future Outlook
- Examples from regulated sectors
- Emerging regulations and compliance trends
- Preparing for evolving enterprise AI standards
Summary and Next Steps
Requirements
- Knowledge of enterprise IT infrastructure
- Experience with data governance or compliance frameworks
- Understanding of security and privacy legislation
Target Audience
- Compliance leads
- Security architects
- Legal and operations stakeholders
