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Duration 14 hours
Course Outline
Introduction to Privacy-Preserving AI
- Foundational principles of data privacy in mobile applications
- Regulatory factors driving the adoption of on-device AI
- Advantages and constraints associated with local data processing
Exploring Nano Banana for On-Device Privacy
- Architectural overview of the Nano Banana model
- Security features and mechanisms for local execution
- Supported platforms and best practices for mobile integration
Techniques for Secure Data Handling and Local Processing
- Methods for safely collecting and storing sensitive data on the device
- Reducing data exposure through local inference capabilities
- Strategies for anonymization and pseudonymization
Deploying Privacy-Preserving AI Capabilities
- Developing AI-driven functionalities that require no external data transmission
- Designing workflows compliant with healthcare, finance, and other regulatory standards
- Ensuring strict data isolation among different application components
Security Considerations for On-Device Models
- Defending models against extraction attempts and tampering
- Implementing secure sandboxing and managing permissions effectively
- Conducting threat modeling specific to mobile AI ecosystems
Aligning with Compliance and Regulatory Standards
- Navigating the implications of GDPR, HIPAA, and financial sector regulations
- Documenting privacy-by-design methodologies
- Maintaining audit trails without exposing user data
Testing and Verifying Privacy Assurances
- Testing workflows to detect any unintended data leaks
- Balancing the trade-offs between model accuracy and privacy
- Implementing continuous validation processes across app updates
Deployment and Ongoing Maintenance of Privacy-Focused AI Apps
- Managing the update cycle for on-device models
- Monitoring performance metrics and compliance status over time
- Preparing applications to adapt to evolving regulatory landscapes
Conclusion and Recommended Next Steps
Requirements
- Foundational knowledge of mobile or application development principles
- Proficiency in Python, Kotlin, or Swift
- Basic familiarity with artificial intelligence and machine learning concepts
Target Audience
- Enterprise technology teams
- Compliance officers
- Developers responsible for building applications handling sensitive data
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 2600 € + VAT*
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