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Course Outline

Getting Started with On-Device AI using Nano Banana

  • Fundamental principles of on-device inference
  • Exploring the Nano Banana model architecture and its capabilities
  • Key deployment considerations for mobile operating systems

Setting Up Nano Banana and the Development Environment

  • Installing the Nano Banana SDK and associated tools
  • Configuring build environments for Android and iOS
  • Handling dependencies and ensuring version compatibility

Executing Nano Banana Models on Mobile Hardware

  • Loading and running pre-built models
  • Navigating memory and computational limits on mobile devices
  • Implementing strategies for real-time inference

Developing AI Features with Nano Banana

  • Incorporating text generation features
  • Building workflows for image generation and editing
  • Processing multimodal inputs within applications

Optimizing Performance and Conducting Benchmarks

  • Profiling latency and throughput
  • Applying quantization, pruning, and model compression methods
  • Optimizing for thermal management, battery life, and resource utilization

Security and Privacy in On-Device AI

  • Managing local data handling and regulatory compliance
  • Safeguarding models through secure execution environments
  • Identifying risks and implementing mitigation strategies

Advanced Deployment Strategies

  • Designing hybrid workflows combining on-device and cloud processing
  • Managing offline-first AI application architectures
  • Scaling solutions for large user bases

Testing, Debugging, and Continuous Refinement

  • Implementing CI/CD pipelines for AI-enabled mobile apps
  • Conducting unit, integration, and performance testing
  • Managing iterative model updates and ensuring backward compatibility

Wrap-up and Future Directions

Requirements

  • A solid grasp of mobile application development principles
  • Proficiency in Python, Kotlin, or Swift
  • Working knowledge of machine learning fundamentals

Target Audience

  • Mobile application developers
  • AI engineers
  • Technical professionals investigating on-device AI deployment strategies
 14 Hours

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