- 13m
- 6m
- 3. Project I: Model Training & Deployment for Light Sensor Gesture Recognition 10m
- 4. Project I: Practical Session Part 1 14m
- 5. Project I: Practical Session Part 2 14m
- 6. Project II: Theory & Data Collection for Hand Gesture Classification Using Accelerometer 7m
- 7. Project II: Model Training & Deployment for Hand Gesture Classification Using Accelerometer 11m
- 8. Project III: Theory & Data Collection for Audio Scene Recognition Using Microphone 10m
- 9. Project III: Model Training & Deployment for Audio Scene Recognition Using Microphone 11m
- 10. Project IV: Theory & Data Collection for People Counting Using Ultrasonic Sensor 6m
- 11. Project IV: Model Training & Deployment for People Counting Using Ultrasonic Sensor 15m
- 12. Project V: Theory & Data Collection for Intelligent Meteostation Using BME280 6m
- 13. Project V: Model Training & Deployment for Intelligent Meteostation Using BME280 7m
- 14. Student Project Showcase 6m
TinyML with Wio Terminal
About this course
Introduction
Welcome to the TinyML with Wio Terminal course!
In this course, you will explore the fascinating world of Tiny Machine Learning (TinyML) using the Wio Terminal. The Wio Terminal, a powerful and versatile microcontroller, provides the perfect platform for implementing TinyML projects that can run machine learning models on small devices.
Throughout this course, you will learn how to:
- Recognize gestures using light sensors.
- Classify hand gestures with accelerometers.
- Perform audio scene recognition using microphones.
- Count people using ultrasonic sensors.
- Build an intelligent meteostation with the BME280 sensor.
This course is structured into several hands-on projects, each focusing on different sensors and machine learning techniques. You'll begin with an introduction to TinyML and the Wio Terminal, followed by detailed theoretical and practical sessions for each project. By the end of this course, you will be equipped with the skills and knowledge to create your own TinyML applications on the Wio Terminal.
Whether you're a beginner or have some experience in machine learning and microcontrollers, this course is designed to guide you step-by-step to master the concepts of TinyML.
So let's get started on this exciting journey of bringing machine learning to tiny devices!
What you'll learn
- Recognize gestures using light sensors.
- Classify hand gestures with accelerometers.
- Perform audio scene recognition using microphones.
- Count people using ultrasonic sensors.
- Build an intelligent meteostation with the BME280 sensor.
Who this course is for
- Enthusiasts interested in Tiny Machine Learning (TinyML)
- Students and hobbyists looking to implement machine learning on small devices
- Developers aiming to expand their knowledge in microcontroller-based projects
- Beginners in machine learning and microcontrollers seeking hands-on projects
Requirements
- Basic knowledge of programming (preferably in Python or C++)
- Familiarity with microcontrollers and sensors
- A computer with internet access
- Wio Terminal device
- Various sensors (light sensor, accelerometer, microphone, ultrasonic sensor, BME280)
Curriculum
14 Lessons • 2h 10m estimated learning time
- 5.00 instructor rating
- 39 courses
- 37 students worldwide
Ashraf S.A Almadhoun
I've always tried to live life presently and to the fullest. Some of the things I love to do in my spare time include football, biking, traveling to new places, watching sports (huge football fan here!), and sharing meals with friends and family.
In 2012, I graduated with my Bachelor of Mechatronics Engineering at Azhar University - one of the top schools in the country. While there, I was fortunate to make Embedded Systems project using Arduino, PIC Microcontroller and other modules. After graduating, I worked at My own university as a Teacher Assistant . I followed that stint with a contract at a local College where I discovered how amazing it is to share your knowledge offline, which made me eager and eventually found myself starting my own online learning journey. I helped more than 100k student since then. Most recently. Throughout this time I built my Educational Engineering School Online brand to teach others the skills that I have. Now I only do things I love each day.
I want to show you how to be a better Embedded System creator, make money from your skills, and live the life you dreamed of.
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