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Course Outline
Advanced Concepts in Edge AI
- Deep dive into Edge AI architecture
- Comparative analysis of Edge AI and cloud AI
- Latest trends and emerging technologies in Edge AI
- Advanced use cases and applications
Advanced Model Optimization Techniques
- Quantization and pruning for edge devices
- Knowledge distillation for lightweight models
- Transfer learning for edge AI applications
- Automating model optimization processes
Cutting-Edge Deployment Strategies
- Containerization and orchestration for Edge AI
- Deploying AI models using edge computing platforms (e.g., Edge TPU, Jetson Nano)
- Real-time inference and low-latency solutions
- Managing updates and scalability on edge devices
Specialized Tools and Frameworks
- Exploring advanced tools (e.g., TensorFlow Lite, OpenVINO, PyTorch Mobile)
- Using hardware-specific optimization tools
- Integrating AI models with specialized edge hardware
- Case studies of tools in action
Performance Tuning and Monitoring
- Techniques for performance benchmarking on edge devices
- Tools for real-time monitoring and debugging
- Addressing latency, throughput, and power efficiency
- Strategies for ongoing optimization and maintenance
Innovative Use Cases and Applications
- Industry-specific applications of advanced Edge AI
- Smart cities, autonomous vehicles, industrial IoT, healthcare, and more
- Case studies of successful Edge AI implementations
- Future trends and research directions in Edge AI
Advanced Ethical and Security Considerations
- Ensuring robust security in Edge AI deployments
- Addressing complex ethical issues in AI at the edge
- Implementing privacy-preserving AI techniques
- Compliance with advanced regulations and industry standards
Hands-On Projects and Advanced Exercises
- Developing and optimizing a complex Edge AI application
- Real-world projects and advanced scenarios
- Collaborative group exercises and innovation challenges
- Project presentations and expert feedback
Summary and Next Steps
Requirements
- In-depth understanding of AI and machine learning concepts
- Proficiency in programming languages (Python recommended)
- Experience with edge computing and deploying AI models on edge devices
Audience
- AI practitioners
- Researchers
- Developers
14 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €4560 online delivery, based on a group of 2 delegates, €1440 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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