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Course Outline

Fundamentals of Privacy-Preserving AI

  • Key principles of data privacy within mobile applications
  • Regulatory factors driving on-device AI adoption
  • Advantages and constraints of local data processing

Exploring Nano Banana for On-Device Privacy

  • Architecture of the Nano Banana model
  • Security features and local execution mechanisms
  • Supported 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
  • Strategies for anonymization and pseudonymization

Building Privacy-Preserving AI Capabilities

  • Creating AI-driven features that avoid transmitting user data
  • Designing workflows compliant with healthcare, financial, and regulatory standards
  • Ensuring data isolation among different app components

Security Perspectives for On-Device Models

  • Safeguarding models against extraction or tampering
  • Implementing secure sandboxing and managing permissions
  • Threat modeling for mobile AI systems

Aligning with Compliance and Regulations

  • Implications of GDPR, HIPAA, and financial sector regulations
  • Documenting privacy-by-design methodologies
  • Ensuring auditability while protecting user data

Verifying and Testing Privacy Assurances

  • Testing workflows to detect unintended data leaks
  • Balancing accuracy against privacy requirements
  • Continuous validation through application updates

Deploying and Maintaining Privacy-Centric AI Applications

  • Overseeing updates to on-device models
  • Tracking performance and compliance metrics over time
  • Future-proofing applications against evolving regulatory landscapes

Wrap-Up and Recommended Next Steps

Requirements

  • Familiarity with mobile or application development
  • Proficiency in Python, Kotlin, or Swift
  • Basic knowledge of AI or machine learning concepts

Target Audience

  • Enterprise teams
  • Compliance officers
  • Developers creating applications handling sensitive data
 14 Hours

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