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Raspberry Pi 및 센서를 사용한 Python에서의 머신 러닝(2단계)

이 10개 수업 프로그램에서 학생들은 Python 코딩과 Raspberry Pi를 사용하여 AD DA 및 전위계, 서미스터, 조이스틱과 같은 다양한 센서를 제어하고 통신하는 방법을 배웁니다.
AI Code Academy
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10개의 라이브 미팅
수업 15 시간
보고계신 지문은 자동 번역 되었습니다

수업 소개

Hardware Coding with Python on Raspberry Pi and Sensors (Level II)

Lesson 1 – LCD Screen
Designed to provide students with an introduction to I2C communication, as well as experience in displaying information on an LCD Screen.
Task: LCD Screen Implementation
Assist students with I2C setup, circuit creation, and development of code which will allow the screen to display the current time and CPU temperature.

Lesson 2 – AD/DA
Designed to provide students with a more in-depth view of various circuit components and I2C communication in conjunction with the concepts of potentiometers, Analog-to-Digital conversion, and Digital-to-Analog conversion.
	Task: Demonstrate AD/DA
	Assist students in the creation of the project circuit and development of code which will 	
	represent the AD/DA conversion process

Lesson 3 – RGB LED
Instruct students on the concepts of the RGB lighting system as well as the circuit components used to generate various combinations of RGB lighting.
	Task: RGB LED Implementation
	Walk students through the programming and circuit configuration necessary in order to 	set up an RGB LED

Lesson 4 – Thermistor
Walk students through the concept of heat-associated resistance and how it can be implemented on the Pi/Circuit.
	Task: Thermistor Setup
	Walk students through the programming and circuit configuration necessary in order to 	set up a thermistor within a circuit.

Lesson 5 –Joystick and Snake
Provide students with an understanding of joystick control and how it can be implemented in code. Perform the circuit setup and code development necessary to monitor joystick positioning. 
Task: Snake Game
Provide students with an introduction to more advanced applications of circuit components, through the use of the previous joystick circuit and the Pygame library.  Walk students through the code required to make a fully functional game of Snake, which can be controlled by a joystick.

Lesson 6 – Attitude Sensor
Provide students with an understanding of the attitude sensor component and its association with the Pi.  Also, discuss new circuit component architectures.
	Task: Attitude Sensor Setup
	Instruct students to create the circuit and generate code in order to create a functional 	attitude sensor.

Lesson 7 – Bar Graph LED
Introduce students to the concept of integrated circuits, serial-to-parallel data communication, and different types of LED components.
	Task: Bar Graph LED Setup
	Walk students through the programming and circuit configuration necessary in order to 	set up 8 LEDs lighting in sequence.

Lesson 8 – 7-Segment Display
Provide students with an understanding of how to use integrated circuits to light up multiple patterns of LEDs, forming letters and numbers.
	Task: 7-Segment Display Setup
	Assist students in developing the circuit and code required to make use of a 7-segment display.

Lesson 9 – Matrix Keypad
Discuss the concept of inputs from circuit components, through the use of a keypad, into a Pi. Also discuss the anatomy of the keypad component.
	Task: Matrix Keypad Setup
	Perform the tasks necessary to create a functional keypad that works in coordination 	with the Pi

Class 10 - Final Project
The students will create their own program applying what they have learned throughout the class. Upon completion, the projects are demonstrated by their creators.




Technical Requirements:
PC (Windows 10) or Mac (macOS 10.13)  with at least a 2GHz processor and 2GB of RAM (4GB of RAM is recommended).
No Chromebook!!!
Broadband internet with at least 1.8Mbps download and 900Kbps upload speeds. Please make sure to remove your firewall if any
Webcam - Either external or built-in (many laptops have an integrated camera).
Microphone and Speakers - We recommend headphones with an integrated microphone 

Prerequisites: Python experience (15 hours at least) and Raspberry Pi experience (10 hours at least) required

Materials needed: we presume you already had the following hardware. If any parts are spoiled please repurchase from Amazon:

1, CanaKit Raspberry Pi 3 Kit with 2.5A Power Supply ($60)    https://www.amazon.com/CanaKit-Raspberry-Premium-Supply-Listed/dp/B01C6EQNNK/ref=sr_1_3?keywords=raspberry+pi+3&qid=1575431887&sr=8-3

2, 32GB microSDHC Class 10 microSD Memory Card ($9)    https://www.amazon.com/Kingston-32GB-microSDHC-microSD-SDCS/dp/B079GTYCW4/ref=sr_1_3?dchild=1&keywords=32GB+microSDHC+Class+10+microSD+Memory+Card&qid=1589205799&s=electronics&sr=1-3

3, Freenove Ultimate Starter Kit for Raspberry Pi 4 B 3 B+ ($50)     https://www.amazon.com/Freenove-Raspberry-Processing-Tutorials-Components/dp/B06W54L7B5/ref=sr_1_1?dchild=1&keywords=freenove+ultimate+starter+kit+for+raspberry+pi+4b+3+b%2B&qid=1589205731&s=electronics&sr=1-1

그 외 세부 사항

학부모 가이드
To join this course, students must have learned how to build physical models using Raspberry Pi and Python, or participated in our Machine Learning in Python with Raspberry Pi and Sensors. You should already have had had Raspberry Pi and Sensors and your Pi has been connected to your computer or a separated monitor/keyboard/mouse
수업 자료
Prerequisites: Python experience (15 hours at least) and Raspberry Pi experience (10 hours at least) required

Materials needed: we presume you already had the following hardware. If any parts are spoiled please repurchase from Amazon:

1, CanaKit Raspberry Pi 3 Kit with 2.5A Power Supply ($60)    https://www.amazon.com/CanaKit-Raspberry-Premium-Supply-Listed/dp/B01C6EQNNK/ref=sr_1_3?keywords=raspberry+pi+3&qid=1575431887&sr=8-3

2, 32GB microSDHC Class 10 microSD Memory Card ($9)    https://www.amazon.com/Kingston-32GB-microSDHC-microSD-SDCS/dp/B079GTYCW4/ref=sr_1_3?dchild=1&keywords=32GB+microSDHC+Class+10+microSD+Memory+Card&qid=1589205799&s=electronics&sr=1-3

3, Freenove Ultimate Starter Kit for Raspberry Pi 4 B 3 B+ ($50)     https://www.amazon.com/Freenove-Raspberry-Processing-Tutorials-Components/dp/B06W54L7B5/ref=sr_1_1?dchild=1&keywords=freenove+ultimate+starter+kit+for+raspberry+pi+4b+3+b%2B&qid=1589205731&s=electronics&sr=1-1

4, If your computer doesn't have a SDHC card port, you also need to purchase a Vanja Micro USB OTG Adapter   https://www.amazon.com/Vanja-Adapter-Portable-Memory-Reader/dp/B00W02VHM6/ref=sr_1_6?crid=27W57S4IKFGO9&dchild=1&keywords=sd+card+to+pc+adapter&qid=1591152969&sprefix=sd+card+to+pc%2Caps%2C149&sr=8-6
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가입일: April, 2020
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At AI Code Academy, we specialize in project-based STEM coding, AI, and mathematics programs for young learners. We are one of the few organizations that offer AI and machine learning courses tailored for kids. Our comprehensive curriculum spans from basic computer skills and Scratch coding to more advanced Python, Java, web design, game development, and AI machine learning projects.

Our unique focus is on introducing students to AI early, helping them grasp complex concepts like machine learning, data analysis, and smart devices, while also reinforcing mathematics skills, essential for their success in STEM fields.

With a team of passionate instructors—college students and recent graduates with degrees in Engineering and Computer Science—we provide hands-on, real-world projects that prepare students for future careers in AI, coding, robotics, and mathematics.

리뷰

실시간 그룹 수업
공유
10 회 수업에

US$279

2주 동안 주당 5회
90분

19 명의 학생이 수업을 완료함
실시간 화상 수업
연령: 11-15
수업당 학습자 5-12 명

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