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Duration 14 hours
Course Outline
Introduction to Privacy-Preserving AI
- Fundamental principles of data privacy in mobile applications
- Regulatory factors driving the shift toward on-device AI
- Advantages and constraints of local processing
Understanding Nano Banana for On-Device Privacy
- Architecture of the Nano Banana model
- Security properties and local execution workflows
- Supported platforms and mobile integration patterns
Data Handling and Local Processing Techniques
- Secure collection and storage of sensitive data on-device
- Reducing data exposure through local inference
- Strategies for anonymization and pseudonymization
Implementing Privacy-Preserving AI Features
- Developing AI features that do not transmit user data externally
- Designing workflows compliant with healthcare, finance, or other regulatory standards
- Ensuring data isolation between different application components
Security Considerations for On-Device Models
- Safeguarding models against extraction or tampering
- Implementing secure sandboxing and permission management
- Conducting threat modeling for mobile AI systems
Compliance and Regulatory Alignment
- Navigating implications of GDPR, HIPAA, and financial sector regulations
- Documenting privacy-by-design methodologies
- Maintaining audit trails without compromising user data security
Testing and Validating Privacy Guarantees
- Testing workflows to detect unintended data leakage
- Assessing the balance between accuracy and privacy
- Performing continuous validation throughout application updates
Deployment and Maintenance of Privacy-Focused AI Apps
- Managing updates for on-device models
- Monitoring performance and compliance over time
- Preparing applications for evolving regulatory landscapes
Summary and Next Steps
Requirements
- Foundational knowledge of mobile or application development
- Proficiency in Python, Kotlin, or Swift
- Basic understanding of AI or machine learning concepts
Audience
- Enterprise technology teams
- Compliance officers
- Developers creating applications handling sensitive data
Testimonials (1)
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