Machine Learning in Python With Raspberry Pi & Sensors (Level 2)

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In this advanced-level course, Machine Learning in Python with Raspberry Pi & Sensors (Level 2), students will dive deeper into coding and hardware integration using the Raspberry Pi. Designed for learners with prior experience in Python and Raspberry Pi, the class covers a variety of hardware projects, from controlling LED lights to using a joystick for a Snake game, and implementing 7-segment displays. Each lesson focuses on hands-on learning, with students setting up circuits and developing code to integrate sensors, displays, and other hardware components.

The course is structured around practical applications of concepts like I2C communication, AD/DA conversion, and PWM control. By the end of the course, students will have completed multiple hardware projects and developed a final project that demonstrates their understanding of both hardware and machine learning fundamentals. Topics include RGB LED lighting, thermistor setup, servo control, and integrated circuits.

What will be taught?

Raspberry Pi hardware setup and coding
I2C communication and AD/DA conversion
Circuit configuration for sensors, LEDs, and displays
Python integration with machine learning models
What topics will be covered?

LCD screen displays, RGB lighting systems, and thermistor circuits
Snake game programming using a joystick
Servo and bar graph LED integration
Creating machine learning models in Python
How is the class structured? Each lesson features a project-based approach, with students completing hands-on tasks to reinforce learning. Lessons build progressively in complexity, starting with basic circuit setups and advancing to full project creation, culminating in a final project where students apply everything they've learned.

For a week-to-week program, check out the syllabus.