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.
Duration 14 hours
Course Outline
Foundations of Privacy-Preserving AI
- Essential principles of data privacy in mobile ecosystems.
- Regulatory factors driving the adoption of on-device AI.
- Advantages and constraints of local data processing.
Nano Banana for On-Device Privacy
- Architecture and structure of the Nano Banana model.
- Security characteristics and local execution pathways.
- Compatible platforms and mobile integration patterns.
Data Management and Local Processing Methods
- Secure collection and storage of sensitive data on the device.
- Reducing data exposure through local inference mechanisms.
- Strategies for anonymization and pseudonymization.
Developing Privacy-Preserving AI Capabilities
- Creating AI-driven features without transmitting user data externally.
- Designing workflows suitable for healthcare, finance, or other regulated industries.
- Ensuring robust data isolation across different app components.
Security Implications for On-Device Models
- Safeguarding models against extraction or tampering attempts.
- Managing secure sandboxes and permissions effectively.
- Applying threat modeling techniques to mobile AI systems.
Aligning with Compliance and Regulatory Standards
- Interpreting the implications of GDPR, HIPAA, and financial-sector regulations.
- Documenting privacy-by-design methodologies.
- Maintaining audit trails without compromising user privacy.
Verifying Privacy Guarantees through Testing
- Testing workflows to detect unintended data leakage.
- Balancing accuracy against privacy trade-offs.
- Performing continuous validation across application updates.
Deploying and Maintaining Privacy-Centric AI Applications
- Overseeing the update process for on-device models.
- Monitoring long-term performance and compliance status.
- Future-proofing applications against evolving regulatory landscapes.
Conclusion and Future Directions
Requirements
- Fundamental knowledge of mobile or application development.
- Proficiency in Python, Kotlin, or Swift.
- Basic understanding of AI or machine learning principles.
Target Audience
- Enterprise development teams.
- Compliance officers and auditors.
- Developers tasked with creating sensitive or regulated applications.
Testimonials (1)
Flow , vibe and topic on presentation
