https://github.com/seeed-studio/seeed_studio_courses

Edge AI 101 Course using Nvidia Jetson
https://github.com/seeed-studio/seeed_studio_courses

ai-education computer-vision edge-ai nvidia-jetson-nano python

Last synced: about 1 year ago
JSON representation

Edge AI 101 Course using Nvidia Jetson

• Host: GitHub
• URL: https://github.com/seeed-studio/seeed_studio_courses
• Owner: Seeed-Studio
• License: mit
• Created: 2021-04-16T08:16:19.000Z (about 5 years ago)
• Default Branch: main
• Last Pushed: 2025-04-03T02:16:15.000Z (about 1 year ago)
• Last Synced: 2025-04-03T03:23:31.889Z (about 1 year ago)
• Topics: ai-education, computer-vision, edge-ai, nvidia-jetson-nano, python
• Language: C++
• Homepage: https://seeed-studio.github.io/Seeed_Studio_Courses/
• Size: 142 MB
• Stars: 54
• Watchers: 11
• Forks: 19
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          


Seeed Studio Courses







Welcome to the **Seeed Studio Courses** repository! This repository contains a collection of educational courses created by Seeed Studio, aimed at helping developers, makers, and students learn about various aspects of AI, IoT, and embedded systems. The courses in this repository provide hands-on exercises, code examples, and instructional content to guide users through various topics.

## Courses Included

Currently, this repository contains the following courses:

### 1. Edge AI 101 with Nvidia Jetson Course

   - **Description**: This course is designed to introduce users to Edge AI with the Nvidia Jetson platform. It covers the basics of AI and how it can be deployed on edge devices for real-time inference and decision-making.

   - **Topics Covered**:

     - Setting up Nvidia Jetson devices

     - Basics of Edge AI and its applications

     - Implementing neural networks on edge devices

     - Running inference and optimizing performance

   - **Audience**: Beginners to intermediate users interested in learning AI on edge devices, specifically using Nvidia Jetson hardware.

### 2. Seeed Arduino WioTerminal TinyML Course

   - **Description**: This course focuses on TinyML, or Tiny Machine Learning, with Seeed Studio’s Wio Terminal. It is aimed at teaching users how to implement simple machine learning models on microcontrollers for IoT applications.

   - **Topics Covered**:

     - Introduction to TinyML and Wio Terminal

     - Setting up the Arduino environment

     - Training and deploying small ML models

     - Building practical applications with TinyML on Wio Terminal

   - **Audience**: Arduino enthusiasts, IoT developers, and beginners interested in ML on microcontrollers.

## Requirements

Each course may have its own set of requirements. Please refer to the respective course folder for specific instructions on hardware, software, and dependencies.

## Contributing

We welcome contributions! If you have ideas for new courses, improvements, or corrections, please feel free to submit a pull request. For major changes, please open an issue first to discuss your ideas.

## License

This repository is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.