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Course Outline

Getting Started with On-Device AI and Nano Banana

  • Foundational concepts of on-device inference
  • Nano Banana model architecture and key features
  • Key considerations for deploying on mobile platforms

Setting Up Nano Banana and the Development Environment

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

Executing Nano Banana Models on Mobile Hardware

  • Loading and running pre-built models
  • Navigating memory and compute limits on mobile devices
  • Strategies for achieving real-time inference

Creating AI-Driven Features with Nano Banana

  • Integrating text generation capabilities
  • Building workflows for image generation and editing
  • Leveraging multimodal inputs within applications

Optimizing Performance and Conducting Benchmarks

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

Addressing Security and Privacy in On-Device AI

  • Local data management and regulatory compliance
  • Protecting models and ensuring secure execution
  • Identifying risks and implementing mitigation strategies

Advanced Deployment Strategies

  • Designing hybrid workflows that combine on-device and cloud processing
  • Managing offline-first AI applications
  • Scaling solutions for large user bases

Testing, Debugging, and Continuous Improvement

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

Conclusion and Future Directions

Requirements

  • A solid understanding of mobile application development
  • Proficiency in Python, Kotlin, or Swift
  • A working knowledge of machine learning fundamentals

Target Audience

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

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