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Course Outline
Introduction to Low-Power AI for Government
- Overview of Artificial Intelligence (AI) in embedded systems for government applications
- Challenges associated with deploying AI on low-power devices in the public sector
- Energy-efficient AI applications relevant to government operations
Model Optimization Techniques for Government Use
- Quantization and its impact on performance in government systems
- Pruning and weight sharing techniques for optimizing models for government use
- Knowledge distillation methods to simplify models for governmental applications
Deploying AI Models on Low-Power Hardware for Government
- Utilizing TensorFlow Lite and ONNX Runtime for edge AI in government systems
- Optimizing AI models with NVIDIA TensorRT for governmental operations
- Leveraging hardware acceleration with Coral TPU and Jetson Nano for government applications
Reducing Power Consumption in AI Applications for Government
- Power profiling and efficiency metrics for government systems
- Low-power computing architectures suitable for government use
- Dynamic power scaling and adaptive inference techniques for governmental applications
Case Studies and Real-World Applications of Low-Power AI in Government
- AI-powered battery-operated IoT devices for government operations
- Low-power AI solutions for healthcare and wearables in the public sector
- Smart city and environmental monitoring applications for governmental use
Best Practices and Future Trends in Low-Power AI for Government
- Optimizing edge AI for sustainability in government operations
- Advancements in energy-efficient AI hardware for government applications
- Future developments in low-power AI research relevant to the public sector
Summary and Next Steps for Government Implementation
Requirements
- An understanding of deep learning models for government applications.
- Experience with embedded systems or the deployment of artificial intelligence solutions.
- Basic knowledge of model optimization techniques.
Audience
- AI engineers working in government agencies.
- Embedded developers supporting public sector projects.
- Hardware engineers involved in government technology initiatives.
21 Hours
