From first boot to GPIO-controlled hardware, Python sensor projects, camera integration, and cloud connectivity. The hands-on Raspberry Pi course for engineers and makers who want to build real things.
This is a text-first course that links out to the best supporting material on the internet instead of trying to replace it. The goal is to make this the best course on raspberry pi you can find — even without producing a single minute of custom video.
This course is built by engineers who ship raspberry pi systems for a living. It reflects how these tools actually behave in production — not how the documentation describes them.
Every day includes working code examples you can copy, run, and modify right now. The goal is understanding through doing, not passive reading.
Instead of re-explaining existing documentation, this course links to the definitive open-source implementations and the best reference material on raspberry pi available.
Each day is designed to finish in about an hour of focused reading plus hands-on work. Do the whole course over a week of lunch breaks. No calendar commitment, no live classes.
Each day stands alone. Read them in order for the full picture, or jump straight to the day that answers the question you have today.
Raspberry Pi OS installation, SSH access, the file system layout, apt package manager, systemd for running services, and the Linux commands you'll use constantly when working on a Pi.
GPIO pin numbering (BCM vs BOARD), digital output to LEDs, digital input with buttons and pull resistors, PWM for motor control, and RPi.GPIO vs gpiozero for simpler Python code.
DHT22 temperature/humidity via one-wire, PIR motion detection, HC-SR04 ultrasonic distance, I2C protocol for multiple sensors on one bus, and reading sensor data into pandas for analysis.
Pi Camera module, capturing images and video with picamera2, running TensorFlow Lite for on-device object detection, and YOLO nano for real-time inference at the edge.
MQTT protocol with Mosquitto, publishing sensor data to AWS IoT or MQTT broker, storing readings in InfluxDB, visualizing with Grafana, and running your Pi project reliably 24/7.
Instead of shooting our own videos, we link to the best deep-dives already on YouTube. Watch them alongside the course. All external, all free, all from builders who ship this stuff.
First boot to SSH access — getting Raspberry Pi OS running and configured for headless development.
Controlling LEDs, reading buttons, PWM motors, and interfacing sensors with RPi.GPIO and gpiozero.
Setting up the Pi Camera, capturing video, and running OpenCV or TensorFlow Lite for on-device computer vision.
Publishing sensor data over MQTT, subscribing to topics, and connecting a Pi to cloud IoT platforms.
Running ML models at the edge — quantized models, inference speed optimization, and practical edge AI projects on Pi hardware.
The best way to deepen understanding is to read the canonical open-source implementations. Clone them, trace the code, understand how the concepts in this course get applied in production.
The standard Python GPIO library for Raspberry Pi. The source shows exactly how Python translates to hardware register writes.
Higher-level GPIO library with a device-focused API. Makes common patterns (LED, Button, Motor, Servo) cleaner than raw RPi.GPIO.
Curated list of Raspberry Pi tools, projects, libraries, and resources across hardware, software, and IoT categories.
The reference Python MQTT client library. Used on Day 5 to publish sensor data from the Pi to an MQTT broker or cloud IoT platform.
You can write Python but you've never controlled physical hardware. This course bridges that gap with GPIO, sensors, and IoT integration.
If you've built Arduino projects and want more — a real Linux OS, Python, networking, and cloud integration — the Raspberry Pi is the natural next step.
The Pi is a practical prototyping platform for IoT products. This course covers the production-oriented patterns — sensor pipelines, MQTT, cloud connectivity — not just blinking LEDs.
The 2-day in-person Precision AI Academy bootcamp covers embedded systems and IoT engineering in depth — hands-on, with practitioners who build AI systems for a living. 5 U.S. cities. $1,490. 40 seats max. June–October 2026 (Thu–Fri).
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