This repository offers a curated collection of Edge AI courses and resources for engineers and practitioners of all levels.
- Start with Edge AI Engineering: a practical guide covering core concepts of the entire Edge AI MLOps stack with industry blueprints.
- Next, read "The Next AI Frontier is at the Edge" to discover Edge AI’s benefits and its rapidly evolving landscape.
- Edge AI is all about solving real-world problems. Get started with these practical, real-world edge-series: Edge Language (Coming Soon!), Edge Audio, Edge Vision
| Course | Description | Level | Price | Organization |
|---|---|---|---|---|
| AIoT Foundations | Learn the full lifecycle of AIoT product development, from use cases to system operation. | Beginner | Paid (cert) | Udacity |
| Fundamentals of Qualcomm AI | Covers fundamentals of AI on Qualcomm platforms, focusing on practical implementation. | Beginner | Free | Qualcomm / GitHub (afondiel) |
| Introduction to On-Device AI | Gain skills to deploy AI on devices, covering model conversion, quantization, and hardware acceleration. | Beginner | Free | Qualcomm / DeepLearning.AI |
| Getting Started with AI on Jetson Nano | Introduces AI development on NVIDIA Jetson Nano, focusing on computer vision and practical projects. | Beginner | Free | NVIDIA DLI |
| Introduction to Embedded ML | A gentle intro to TinyML, deploying models to microcontrollers, and using Edge Impulse. | Beginner | Free (audit) or Paid (cert) | Edge Impulse / Coursera |
| Device-based Models with TensorFlow Lite | Learn to execute ML models on battery-operated devices (Android, iOS, Raspberry Pi, microcontrollers). | Intermediate | Paid (for certificate) | DeepLearning.AI / Coursera |
| ESE3600 tinyML | Intro to ML and Embedded IoT Devices; covers ML applications on embedded hardware. | Intermediate | Course specific, part of UPenn curriculum | University of Pennsylvania (UPenn) |
| TensorFlow Data and Deployment Specialization | Learn to navigate ML model deployment scenarios and effectively use data for training. | Intermediate | Paid (subscription or course) | Google / DeepLearning.AI |
| Intel Edge-AI Certification | Hands-on training with Intel edge AI tools (OpenVINO toolkit, DevCloud) for certification. | Intermediate | Paid (for certification assessment) | Intel |
| Hello AI World | A project for real-time AI inference on NVIDIA Jetson, with examples for computer vision models. | Intermediate | Free | NVIDIA / GitHub (dusty-nv) |
| CS249r tinyML | In-depth course on TinyML applications, algorithms, hardware, and software. | Advanced | Course specific, part of Harvard curriculum | Harvard |
| Intel Edge-AI for IoT Developers (Nanodegree-nd131) | Develop high-performance computer vision and deep learning apps for edge devices using OpenVINO. | Advanced | (Nanodegree price) | Udacity |
| MIT 6.5940 Efficient ML and TinyML | Focuses on efficient ML, covering model compression, quantization, and on-device fine-tuning. | Advanced | Free (part of MIT curriculum) | MIT HAN Lab |
| Edge-ai and edge-cv | Generic Udemy course on Edge AI/CV. | Varied | Varied (often discounted) | Udemy |
If you are aware of an exceptional Edge AI course or resource not yet listed here, or have suggestions for enhancing this repository, please feel free to open an issue or submit a pull request.
For detailed guidelines on how to contribute effectively, please consult our contribution guide.
Let's make Edge AI Engineering accessible to everyone! 🚀