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Course Outline
Introduction to On-Device AI for Government with Nano Banana
- Core principles of on-device inference for government applications
- Nano Banana model architecture and capabilities tailored for public sector use
- Deployment considerations for mobile platforms in government environments
Nano Banana Setup and Development Environment for Government
- Installing Nano Banana SDK tools for government systems
- Configuring Android and iOS build environments for secure government operations
- Managing dependencies and version compatibility in government IT infrastructures
Running Nano Banana Models on Mobile Devices for Government Use
- Loading and executing prebuilt models in a secure, government-compliant manner
- Addressing memory and compute constraints on mobile hardware used by government agencies
- Implementing real-time inference strategies for efficient public sector operations
Building AI Features with Nano Banana for Government Applications
- Integrating text generation functionalities to support government communications and documentation
- Implementing image generation and editing workflows for public sector use cases
- Combining multimodal inputs in apps to enhance user experience and operational efficiency for government services
Performance Optimization and Benchmarking for Government AI Solutions
- Latency and throughput profiling to ensure responsive government applications
- Quantization, pruning, and model compression techniques to optimize performance in resource-constrained environments
- Thermal, battery, and resource usage optimization for sustainable public sector operations
Security and Privacy in On-Device AI for Government
- Local data handling and compliance considerations to meet government regulations
- Model protection and secure execution to safeguard sensitive information
- Risk assessment and mitigation strategies to ensure robust security in government applications
Advanced Deployment Patterns for Government AI Applications
- Hybrid on-device and cloud workflows to balance local processing with centralized data management
- Managing offline-first AI applications to support government operations in areas with limited connectivity
- Scaling for large user bases to accommodate the needs of extensive public sector networks
Testing, Debugging, and Continuous Improvement for Government AI Projects
- CI/CD pipelines for continuous integration and deployment of AI-enabled mobile apps in government settings
- Unit, integration, and performance testing to ensure reliability and efficiency of government applications
- Iterative model updates and backward compatibility to maintain consistent service delivery in the public sector
Summary and Next Steps for Government AI Initiatives
Requirements
- A comprehensive understanding of mobile application development for government use
- Practical experience with programming languages such as Python, Kotlin, or Swift
- Familiarity with fundamental machine learning concepts and techniques
Audience
- Mobile developers for government projects
- AI engineers working in the public sector
- Technical professionals interested in deploying on-device AI solutions for government applications
14 Hours
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