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Course Outline

Foundations of Privacy-Preserving AI

  • Fundamental data privacy principles in mobile apps
  • Regulatory factors driving the adoption of on-device AI
  • Advantages and constraints of local data processing

Nano Banana for On-Device Privacy: An Overview

  • Architectural details of the Nano Banana model
  • Security features and local execution pathways
  • Compatible platforms and mobile integration strategies

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 data anonymization and pseudonymization

Deploying Privacy-Preserving AI Capabilities

  • Developing AI features that avoid transmitting user data
  • Constructing workflows suitable for healthcare, finance, or compliance sectors
  • Safeguarding data isolation between different app modules

Security Aspects for On-Device Models

  • Defending models against extraction or tampering attempts
  • Implementing secure sandboxing and permission controls
  • Conducting threat modeling for mobile AI architectures

Regulatory Compliance and Alignment

  • Navigating GDPR, HIPAA, and financial sector regulatory implications
  • Documenting privacy-by-design methodologies
  • Preserving audit trails without endangering user privacy

Verification and Validation of Privacy Assurance

  • Testing workflows to detect potential data leaks
  • Assessing the balance between model accuracy and privacy
  • Performing ongoing validation throughout app iterations

Releasing and Maintaining Privacy-Focused AI Applications

  • Overseeing on-device model updates and maintenance
  • Tracking performance and compliance standards over time
  • Preparing applications for future regulatory changes

Conclusion and Future Directions

Requirements

  • Familiarity with mobile or application development practices
  • Proficiency in Python, Kotlin, or Swift
  • Fundamental knowledge of AI or machine learning principles

Target Audience

  • Corporate teams
  • Compliance professionals
  • Engineers developing applications involving sensitive data
 14 Hours

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