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Course Outline

Introduction to Privacy-Preserving AI

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

Exploring Nano Banana for On-Device Privacy

  • Nano Banana model architecture
  • Security features and local execution mechanisms
  • Compatible platforms and mobile integration strategies

Data Management and Local Processing Methods

  • Securely collecting and retaining sensitive data on the device
  • Reducing data exposure through local inference
  • Strategies for anonymization and pseudonymization

Deploying Privacy-Preserving AI Features

  • Developing AI-driven functionalities that avoid transmitting user data
  • Designing workflows suitable for healthcare, finance, or compliance requirements
  • Guaranteeing data segregation across different application components

Security Aspects of On-Device Models

  • Safeguarding models against extraction or alteration
  • Implementing secure sandboxing and permission controls
  • Threat modeling for mobile AI systems

Regulatory Compliance and Alignment

  • Navigating GDPR, HIPAA, and financial sector regulations
  • Documenting privacy-by-design methodologies
  • Preserving audit capabilities without endangering user data

Testing and Verifying Privacy Safeguards

  • Assessing workflows to detect unintended data leaks
  • Weighing the balance between accuracy and privacy
  • Ongoing verification across application updates

Deployment and Sustaining Privacy-Centric AI Applications

  • Handling on-device model updates
  • Tracking performance and compliance consistency over time
  • Preparing applications for future regulatory changes

Wrap-Up and Future Directions

Requirements

  • A foundational understanding of mobile or application development
  • Proficiency in Python, Kotlin, or Swift
  • Basic knowledge of AI or machine learning principles

Target Audience

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

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