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Duration 14 hours
Course Outline
Foundations of Privacy-Preserving AI
- Essential principles of data privacy within mobile applications.
- Regulatory factors driving the shift toward on-device AI.
- Advantages and constraints of local data processing.
Nano Banana for On-Device Privacy
- Architectural overview of the Nano Banana model.
- Security characteristics and local execution mechanisms.
- Compatible platforms and mobile integration approaches.
Data Management and Local Processing Methods
- Secure collection and storage of sensitive data on the device.
- Reducing data exposure through local inference techniques.
- Strategies for anonymization and pseudonymization.
Developing Privacy-Preserving AI Capabilities
- Creating AI-driven features that avoid transmitting user data externally.
- Designing workflows suitable for healthcare, finance, and compliance requirements.
- Maintaining data isolation across different application components.
Security Protocols for On-Device Models
- Safeguarding models against extraction or manipulation.
- Implementing secure sandboxing and managing permissions.
- Threat modeling specific to mobile AI systems.
Alignment with Compliance and Regulations
- Navigating GDPR, HIPAA, and financial sector regulatory impacts.
- Documenting privacy-by-design methodologies.
- Preserving audit trails without compromising user privacy.
Testing and Verifying Privacy Assurances
- Testing workflows to prevent unintended data leakage.
- Balancing model accuracy against privacy requirements.
- Performing continuous validation through application updates.
Deployment and Ongoing Maintenance of Privacy-First AI Apps
- Managing updates for on-device models.
- Tracking performance and compliance status over time.
- Adapting applications to keep pace with evolving regulations.
Wrap-Up and Future Pathways
Requirements
- Fundamental knowledge of mobile or application development.
- Proficiency in Python, Kotlin, or Swift.
- Basic grasp of AI or machine learning principles.
Target Audience
- Enterprise development teams.
- Compliance and governance officers.
- Developers working on applications handling sensitive data.
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