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Course Outline

Foundations of On-Device AI using Nano Banana

  • Fundamental concepts behind on-device inference
  • Insights into the Nano Banana model's architecture and features
  • Key deployment factors for mobile operating systems

Configuring the Nano Banana Development Environment

  • Installation of Nano Banana SDK utilities
  • Setting up build environments for Android and iOS
  • Handling dependencies and ensuring version compatibility

Executing Nano Banana Models on Mobile Hardware

  • Loading and running pre-configured models
  • Navigating memory and processing limits on mobile devices
  • Techniques for achieving real-time inference

Creating AI-Driven Features with Nano Banana

  • Integrating text generation capabilities
  • Building workflows for image creation and manipulation
  • Handling multimodal inputs within applications

Enhancing Performance and Conducting Benchmarks

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

Addressing Security and Privacy in On-Device AI

  • Managing local data processing and regulatory compliance
  • Safeguarding models and ensuring secure execution
  • Identifying risks and implementing mitigation measures

Advanced Deployment Strategies

  • Designing hybrid workflows combining on-device and cloud services
  • Developing offline-first AI applications
  • Scaling solutions for extensive user populations

Testing, Debugging, and Ongoing Refinement

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

Conclusions and Future Directions

Requirements

  • A solid grasp of mobile application development processes
  • Proficiency in Python, Kotlin, or Swift
  • A foundational understanding of machine learning principles

Intended Participants

  • Mobile application developers
  • AI engineers
  • Technical specialists investigating on-device AI implementations
 14 Hours

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