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 £3800 online delivery, based on a group of 2 delegates, £1200 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

Contact us for an exact quote and to hear our latest promotions


Public Training

Please see our public courses

Need help picking the right course?

Provisional Upcoming Courses (Contact Us For More Information)

Advanced Edge AI Techniques

2025-10-20 09:30
14 hours
Bradford

Advanced Edge AI Techniques

2025-11-03 09:30
14 hours
Exeter

Advanced Edge AI Techniques

2025-11-17 09:30
14 hours
Leicester

Advanced Edge AI Techniques

2025-12-01 09:30
14 hours
York

Advanced Edge AI Techniques

2025-12-15 09:30
14 hours
Coventry

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