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Starts 24 June 2025 21:17

Ends 24 June 2025

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AI on the Edge

Explore edge computing and AI for building intelligent offline apps. Learn about the AI Toolkit for Azure IoT Edge and create image classifiers using various techniques for offline deployment.
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Overview

Explore edge computing and AI for building intelligent offline apps. Learn about the AI Toolkit for Azure IoT Edge and create image classifiers using various techniques for offline deployment.

Syllabus

  • Introduction to Edge Computing
  • Definition and benefits of edge computing
    Key differences between edge and cloud computing
  • Overview of AI in Edge Computing
  • Use cases for AI on the edge
    Challenges and opportunities
  • Introduction to Azure IoT Edge
  • Overview of the Azure IoT Edge platform
    Setting up Azure IoT Edge environment
  • AI Toolkit for Azure IoT Edge
  • Components of the AI Toolkit
    Integrating AI models into IoT Edge
  • Image Classification on the Edge
  • Basics of image classification
    Popular image classification algorithms
  • Creating Image Classifiers
  • Supervised learning techniques
    Transfer learning for image classification
  • Developing Offline AI Applications
  • Designing AI models for offline use
    Optimizing models for performance on edge devices
  • Deployment of AI Models on Edge Devices
  • Packaging and deploying AI models
    Managing AI models and updates on edge devices
  • Hands-on Project
  • Building a simple image classifier for offline deployment
    Testing and evaluating the model on edge devices
  • Best Practices and Future Trends
  • Best practices for edge AI deployment
    Emerging trends in AI and edge computing technologies
  • Course Conclusion and Q&A
  • Recap of key concepts
    Open floor for questions and discussion

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