Build Production Edge AI Pipeline
EdgeAI from fundamentals to advanced, in one build. Start with raw sensor data on an ESP32 or STM32 — leave having trained, quantized, and deployed a model to a Raspberry Pi or Jetson, with live predictions running on a real dashboard.
Curriculum
Wire a sensor to the ESP32, read raw values, and build a clean preprocessing pipeline ready for model input.
Train a model on collected sensor data, then quantize it to int8 for on-device deployment.
Deploy the quantized model to a Raspberry Pi and validate on-device accuracy against your training results.
Stream predictions over MQTT and build a real-time dashboard to visualize live results.
Handle edge cases, add basic OTA update support, and review the system end to end.
What you'll build
This course follows one complete system from start to finish — not a series of disconnected exercises. By the end, you'll have a real, deployed pipeline: a sensor feeding data through a trained and quantized model, running live inference on hardware, with predictions visible on a dashboard.
Every module builds directly on the last. Each lesson ends with something working, and every project is a checkpoint toward the final system.
One subscription. Every course. Real projects.
Included with an Analog Data subscription. Includes the course, linked projects, source code, and future updates.
FAQ
The course can be followed without hardware, but to experience the hands-on build you will need the relevant components, such as an ESP32 or STM32 board, sensors, and a Raspberry Pi or Jetson. Hardware is purchased separately from different online sellers, so you can choose the exact boards and components that fit your setup.
Your Analog Data subscription unlocks this course, every other course, and the linked projects as they are published. It is the only way to access the course library.
You need basic Python, not embedded experience. The course explains every hardware concept from first principles as you go.
Your instructor
Stop watching. Start shipping.
Real hardware. Real projects. A production Edge AI pipeline that makes your profile stand out.
