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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 mechanisms.
  • Supported platforms and mobile integration patterns.

Data Handling and Local Processing Techniques

  • Secure collection and storage of sensitive data on-device.
  • Minimizing data exposure through local inference.
  • Strategies for anonymization and pseudonymization.

Implementing Privacy-Preserving AI Features

  • Creating AI-driven features without transmitting user data.
  • Designing workflows suitable for healthcare, finance, and compliance sectors.
  • Ensuring data isolation across application components.

Security Considerations for On-Device Models

  • Protecting models from extraction or tampering.
  • Secure sandboxing and permission management.
  • Threat modeling for mobile AI systems.

Compliance and Regulatory Alignment

  • Understanding implications of GDPR, HIPAA, and financial sector regulations.
  • Documenting privacy-by-design approaches.
  • Maintaining auditability without compromising user data.

Testing and Validating Privacy Guarantees

  • Testing workflows to prevent unintended data leakage.
  • Evaluating the trade-offs between accuracy and privacy.
  • Continuous validation across application 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.
  • Proficiency in Python, Kotlin, or Swift.
  • Basic familiarity with artificial intelligence or machine learning concepts.

Target Audience

  • Enterprise development teams.
  • Compliance officers.
  • Developers working on applications handling sensitive data.
 14 Hours

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