Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Privacy-Preserving AI
- Core principles of data privacy in mobile applications.
- Regulatory drivers necessitating on-device AI.
- Advantages and limitations of local processing.
Understanding Nano Banana for On-Device Privacy
- Nano Banana model architecture.
- Security properties and local execution paths.
- Supported platforms and mobile integration patterns.
Data Handling and Local Processing Techniques
- Securely collecting and storing sensitive data on-device.
- Reducing data exposure through local inference.
- Strategies for anonymization and pseudonymization.
Implementing Privacy-Preserving AI Features
- Developing AI-driven features without transmitting user data.
- Designing workflows ready for healthcare, finance, or compliance standards.
- Ensuring data isolation across various app components.
Security Considerations for On-Device Models
- Protecting models from extraction or tampering.
- Implementing secure sandboxing and permission management.
- Conducting threat modeling for mobile AI systems.
Compliance and Regulatory Alignment
- Understanding GDPR, HIPAA, and financial-sector implications.
- Documenting privacy-by-design approaches.
- Maintaining auditability without compromising user data.
Testing and Validating Privacy Guarantees
- Testing workflows to detect unintended data leakage.
- Evaluating the trade-off between accuracy and privacy.
- Ensuring continuous validation across app updates.
Deployment and Maintenance of Privacy-Focused AI Apps
- Managing on-device model updates.
- Monitoring performance and compliance over time.
- Future-proofing applications for evolving regulations.
Summary and Next Steps
Requirements
- A foundational understanding of mobile or application development.
- Experience with Python, Kotlin, or Swift.
- Basic familiarity with AI or machine learning concepts.
Target Audience
- Enterprise teams.
- Compliance officers.
- Developers creating applications that handle sensitive data.
14 Hours
Testimonials (1)
Flow , vibe and topic on presentation
