AI on the Edge

Übersicht

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.

Lehrplan

• 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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Fachgebiete

Conference Talks