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Introduction to Edge AI

Edge AI combines artificial intelligence (AI) and machine learning (ML) with edge computing to enable unique solutions to difficult problems. Advances in ML have enabled smaller and more efficient deep learning models to run on lightweight computing equipment, and advances in computing technology enable faster and more energy-efficient processing on smaller hardware. Edge AI can be found in a variety of applications, including smart speakers, wearable fitness tracking, fall detection, and power grid anomaly detection. This course will provide an overview of edge computing, machine learning, edge AI, MLOps, and several case studies. Each video has an associated written article with a quiz that you can take to test your understanding. At the end of the course, you can find a comprehensive test. If you pass, you will receive a free digital certificate demonstrating the completion of the course. You can read more about this introduction and take a practice quiz here: https://docs.edgeimpulse.com/docs/con... Questions about Edge Impulse and Edge AI can be asked on our forums: https://forum.edgeimpulse.com/ The course is divided into 10 parts: 1. What is edge computing? https://docs.edgeimpulse.com/docs/con... 2. What is machine learning (ML)? https://docs.edgeimpulse.com/docs/con... 3. What is edge AI? https://docs.edgeimpulse.com/docs/con... 4. How to choose an edge AI device: https://docs.edgeimpulse.com/docs/con... 5. Edge AI lifecycle: https://docs.edgeimpulse.com/docs/con... 6. What is edge MLOPs? https://docs.edgeimpulse.com/docs/con... 7. What is Edge Impulse? https://docs.edgeimpulse.com/docs/con... 8. Case study: power grid anomaly detection with Izoelectro: https://docs.edgeimpulse.com/docs/con... 9. Case study with Tunstall Healthcare: coming soon! 10. Going further: https://docs.edgeimpulse.com/docs/con... Chapters: 0:00 Introduction 0:23 Examples of edge AI 1:04 Course overview 2:55 Instructor introduction 3:11 Resources