Embedded AI Learning Path

Freshman Year: Introduction to Arduino (3-6 months)

1. Learning Content

• Basic Electronics: Use of resistors/capacitors/sensors

• Basics of C Language: Variables, loops, functions

• Arduino IDE Development: GPIO control, PWM output

• Communication Protocols: UART, I2C (e.g., driving OLED screens)

2. Recommended Resources

• Textbook: “Arduino from Beginner to Master”

• Video: Bilibili “Zhengdian Atom Arduino Tutorial”

• Hardware: Arduino Uno + sensor kit (approximately 200 RMB)

3. Practical Projects

• Smart Temperature Control Fan (temperature sensor + PWM speed control)

• Bluetooth Remote-Controlled Car (HC-05 module)

—

Sophomore Year: Advanced STM32 (6-12 months)

1. Learning Content

• Register/library function development

• RTOS real-time systems (FreeRTOS task scheduling)

• Hardware peripherals: ADC/DMA/TIM

• Industrial Protocols: Modbus, CAN bus

2. Recommended Resources

• Development Board: STM32F407ZGT6 (with Ethernet)

• Reference Book: “STM32 Library Development Practical Guide”

• Competition: National College Student Electronic Design Competition

3. Practical Projects

• IoT Weather Station (4G module for data upload)

• Robotic Arm Controller (PID algorithm + stepper motor drive)

—

Junior Year: Embedded AI Leap (12+ months)

1. Learning Content

• Edge Computing Framework: TensorFlow Lite Micro

• Model Deployment: Quantization/pruning techniques (e.g., MobileNetV3)

• Multimodal Processing: OpenCV + microphone array

• Domestic Platform: Huawei Ascend NPU development

2. Recommended Resources

• Hardware: NVIDIA Jetson Nano (approximately 800 RMB)

• Course: Coursera “Edge AI”

• Open Source Project: Edge Impulse model training platform

3. Practical Projects

• Smart Access Control (facial recognition + liveness detection)

• Industrial Defect Detection (YOLOv5 + industrial camera)

—

Key Connection Suggestions

1. Validate abilities through competitions at each stage (e.g., participate in the “China Robotics and Artificial Intelligence Competition” in junior year)

2. Start participating in mentor research projects in sophomore year (e.g., the biosensor topic mentioned in the document)

3. Technology stack layering: STM32 + Python (MicroPython) → STM32 + AI (CMSIS-NN library)

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