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Course Outline
Introduction to Privacy-Preserving AI for Government
- Core principles of data privacy in mobile applications for government
- Regulatory drivers for on-device AI in the public sector
- Benefits and limitations of local processing for government operations
Understanding Nano Banana for On-Device Privacy for Government
- Nano Banana model architecture for government applications
- Security properties and local execution paths in government systems
- Supported platforms and mobile integration patterns for government use
Data Handling and Local Processing Techniques for Government
- Collecting and storing sensitive data securely on-device for government operations
- Minimizing data exposure using local inference in government applications
- Anonymization and pseudonymization strategies for government data
Implementing Privacy-Preserving AI Features for Government
- Creating AI-driven features without transmitting user data for government services
- Designing healthcare-, finance-, or compliance-ready workflows for government agencies
- Ensuring data isolation across app components in government applications
Security Considerations for On-Device Models for Government
- Protecting models from extraction or tampering in government systems
- Secure sandboxing and permission management for government apps
- Threat modeling for mobile AI systems in the public sector
Compliance and Regulatory Alignment for Government
- Understanding GDPR, HIPAA, and financial-sector implications for government operations
- Documenting privacy-by-design approaches for government projects
- Maintaining auditability without compromising user data in government systems
Testing and Validating Privacy Guarantees for Government
- Testing workflows for unintended data leakage in government applications
- Evaluating accuracy vs privacy trade-offs for government use cases
- Continuous validation across app updates for government systems
Deployment and Maintenance of Privacy-Focused AI Apps for Government
- Managing on-device model updates in government applications
- Monitoring performance and compliance over time in government systems
- Future-proofing applications for evolving regulations in the public sector
Summary and Next Steps for Government
Requirements
- An understanding of mobile or application development for government systems.
- Experience with Python, Kotlin, or Swift in a public sector context.
- Basic familiarity with AI or machine learning concepts relevant to government operations.
Audience
- Government enterprise teams
- Compliance officers for government agencies
- Developers building sensitive applications for government use
14 Hours
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