Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to On-Device Artificial Intelligence
- Fundamentals of on-device machine learning for government applications
- Advantages and challenges of small language models in public sector operations
- Overview of hardware constraints in mobile and IoT devices for government use
Model Optimization for On-Device Deployment
- Techniques for model quantization and pruning to enhance performance
- Knowledge distillation methods to create smaller, more efficient models for government applications
- Strategies for selecting and adapting models to optimize on-device performance in public sector environments
Platform-Specific AI Tools and Frameworks
- Introduction to TensorFlow Lite and PyTorch Mobile for government use
- Utilizing platform-specific libraries to support on-device AI in public sector projects
- Cross-platform deployment strategies to ensure interoperability in government systems
Real-Time Inference and Edge Computing
- Techniques for achieving fast and efficient inference on devices for government operations
- Leveraging edge computing to enhance on-device AI capabilities for public sector use
- Case studies of real-time AI applications in government agencies
Power Management and Battery Life Considerations
- Optimizing AI applications to ensure energy efficiency for government devices
- Balancing performance and power consumption in public sector on-device solutions
- Strategies for extending battery life in AI-powered devices used by government agencies
Security and Privacy in On-Device AI
- Ensuring data security and user privacy in government applications
- On-device data processing to preserve privacy in public sector operations
- Secure methods for model updates and maintenance in government systems
User Experience and Interaction Design
- Designing intuitive AI interactions for users of government devices
- Integrating language models with user interfaces to enhance usability in public sector applications
- Conducting user testing and gathering feedback on on-device AI solutions for government use
Scalability and Maintenance
- Managing and updating models on deployed devices to ensure ongoing performance in public sector operations
- Strategies for scalable on-device AI solutions to meet the needs of government agencies
- Implementing monitoring and analytics tools to support the deployment of AI systems for government use
Project and Assessment
- Developing a prototype in a chosen domain and preparing it for deployment on a selected device for government application
- Presenting the on-device AI solution to stakeholders within the public sector
- Evaluating the project based on efficiency, innovation, and practicality for government use
Summary and Next Steps
Requirements
- A solid understanding of machine learning and deep learning principles
- Proficiency in Python programming for government
- Fundamental knowledge of hardware limitations for AI deployment
Audience
- Machine learning engineers and artificial intelligence developers
- Embedded systems engineers with an interest in AI applications
- Product managers and technical leads responsible for overseeing AI projects
21 Hours
