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Course Outline

Foundations of Privacy-Preserving AI

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

Mastering Nano Banana for Device-Level Privacy

  • Overview of the Nano Banana model architecture
  • Key security features and local execution mechanisms
  • Compatible platforms and standard mobile integration patterns

Data Management and Local Processing Strategies

  • Securely collecting and retaining sensitive data on the device
  • Reducing data exposure through local inference techniques
  • Applying anonymization and pseudonymization methodologies

Building Privacy-Centric AI Capabilities

  • Developing AI features that require no user data transmission
  • Constructing workflows ready for healthcare, finance, or other regulated industries
  • Safeguarding data isolation between different application components

Securing On-Device Models

  • Defending models against extraction attempts or tampering
  • Implementing secure sandboxing and managing permissions effectively
  • Conducting threat modeling specific to mobile AI ecosystems

Aligning with Compliance and Regulations

  • Navigating the impact of GDPR, HIPAA, and financial-sector standards
  • Documenting privacy-by-design methodologies
  • Preserving audit trails without compromising user confidentiality

Validating Privacy Assurance

  • Testing workflows to detect any unintended data leaks
  • Balancing model accuracy against privacy requirements
  • Ensuring continuous validation throughout app iterations

Deploying and Maintaining Privacy-First AI Applications

  • Overseeing the update cycle for on-device models
  • Tracking long-term performance and compliance adherence
  • Preparing applications for upcoming regulatory changes

Key Takeaways and Path Forward

Requirements

  • A solid grasp of mobile or general application development principles
  • Proficiency in Python, Kotlin, or Swift
  • Fundamental knowledge of AI and machine learning concepts

Target Audience

  • Corporate technology teams
  • Compliance and governance specialists
  • Engineers developing applications handling sensitive data
 14 Hours

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