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Duration 14 hours
Course Outline
Foundations of Privacy-Preserving AI
- Essential data privacy principles in mobile application design.
- Regulatory factors driving the adoption of on-device AI.
- Advantages and constraints of local data processing.
Exploring Nano Banana for On-Device Privacy
- Architectural overview of Nano Banana models.
- Security characteristics and local execution mechanisms.
- Compatible platforms and patterns for mobile integration.
Techniques for Data Handling and Local Processing
- Securely collecting and storing sensitive data on the device.
- Reducing data exposure through local inference.
- Strategies for anonymization and pseudonymization.
Building Privacy-Preserving AI Features
- Developing AI-driven functionalities that do not transmit user data externally.
- Designing workflows suitable for healthcare, finance, or compliance-sensitive sectors.
- Ensuring data isolation across various application components.
Security Aspects of On-Device Models
- Safeguarding models against extraction or tampering.
- Implementing secure sandboxing and managing permissions effectively.
- Conducting threat modeling for mobile AI systems.
Aligning with Compliance and Regulations
- Navigating the implications of GDPR, HIPAA, and financial sector regulations.
- Documenting privacy-by-design methodologies.
- Maintaining audit capabilities without compromising user privacy.
Verifying Privacy Guarantees through Testing
- Testing workflows to identify potential data leakage.
- Balancing accuracy and privacy trade-offs during evaluation.
- Performing continuous validation throughout app updates.
Deploying and Maintaining Privacy-Focused AI Apps
- Overseeing the update process for on-device models.
- Monitoring long-term performance and compliance status.
- Preparing applications for future regulatory changes.
Conclusion and Path Forward
Requirements
- A solid grasp of mobile or application development principles.
- Proficiency in Python, Kotlin, or Swift.
- Foundational knowledge of AI or machine learning concepts.
Target Audience
- Enterprise teams.
- Compliance professionals.
- Developers creating sensitive applications.
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