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Course Outline

Foundations of On-Device AI with Nano Banana

  • Essential concepts of on-device inference
  • Overview of Nano Banana’s model architecture and features
  • Key deployment factors for mobile ecosystems

Setting Up Nano Banana and the Development Workspace

  • Installing the necessary Nano Banana SDK components
  • Preparing Android and iOS build configurations
  • Handling dependency management and version alignment

Executing Nano Banana Models on Mobile Hardware

  • Loading and running pre-optimized models
  • Navigating memory and computational limits on mobile chips
  • Strategies for real-time inference execution

Developing AI Capabilities with Nano Banana

  • Integrating text generation modules
  • Creating workflows for image generation and editing
  • Processing combined multimodal data inputs in applications

Optimizing Performance and Conducting Benchmarks

  • Analyzing latency and throughput metrics
  • Applying quantization, pruning, and model compression methods
  • Improving thermal management, battery life, and resource utilization

Ensuring Security and Privacy in On-Device AI

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

Advanced Deployment Strategies

  • Designing hybrid workflows that combine on-device and cloud resources
  • Managing AI applications with an offline-first approach
  • Scaling solutions to support extensive user bases

Testing, Debugging, and Continuous Enhancement

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

Recap and Future Directions

Requirements

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

Target Audience

  • Mobile software developers
  • AI engineers
  • Technical professionals interested in deploying on-device AI solutions
 14 Hours

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