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Course Outline
Introduction to Responsible AI with Mistral
- Principles of responsible AI
- Mistral enterprise features and roadmap
- Compliance drivers and global regulatory landscape
Privacy and Data Protection
- Techniques for anonymisation and pseudonymisation
- Encryption at rest and in transit
- Managing data access and minimising risk
Data Residency Strategies
- Regional hosting options
- 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 enterprise IT systems
Auditability and Governance
- Setting up audit logs and monitoring
- Governance playbooks for AI systems
- Incident response and escalation workflows
Vendor Options and Deployment Models
- Comparing Mistral self-hosting and managed services
- Evaluating vendor compliance assurances
- Trade-offs in cost, performance, and regulatory alignment
Case Studies and Future Outlook
- Examples from regulated industries
- Emerging regulations and compliance trends
- Preparing for evolving enterprise AI standards
Summary and Next Steps
Requirements
- A solid understanding of enterprise IT systems
- Experience with data governance or compliance frameworks
- Familiarity with security and privacy regulations
Audience
- Compliance leads
- Security architects
- Legal and operations stakeholders
14 Hours
