Raspberry Pi 및 센서를 사용한 Python에서의 머신 러닝(레벨 1)
이 Python 과정에서 학생들은 Raspberry Pi와 센서를 사용하여 머신 러닝과 하드웨어 통합을 배웁니다. 실습 프로젝트를 통해 LED 깜박임에서 동작 감지에 이르기까지 코딩, 회로 및 모델 생성을 탐구합니다.
AI Code Academy
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10개의 라이브 미팅
수업 10 시간프로젝트
주당 2-4시간. Projects are not mandatory but we strongly encourage students to complete them학습 평가
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수업 종료 후 1회보고계신 지문은 자동 번역 되었습니다
수업 소개
This course provides an exciting introduction to machine learning, Python programming, and hardware integration using the Raspberry Pi. Over 10 hands-on lessons, students will learn the basics of setting up the Raspberry Pi, understanding its operating system, and working with various electronic components such as LEDs, buzzers, servos, and motion sensors. What will be taught? Students will gain practical experience in both coding and electronics. They will be introduced to the basics of machine learning, Python, and hardware components, with an emphasis on how to use these tools to create real-world projects. The course culminates in a machine learning project where students will build and use their own model. Topics Covered: Raspberry Pi setup and basic networking Python programming for Raspberry Pi Circuitry basics and using components like LEDs, buzzers, and sensors Pulse Width Modulation (PWM) and controlling servos Creating machine learning models using AICode101 Hands-on projects including motion detection and ultrasonic ranging How is the class structured? Each lesson is project-based, providing students with clear, step-by-step instructions to build and code their own projects. Lessons progress in complexity, ensuring that students gradually develop their skills in Python, electronics, and machine learning. The course is designed to balance theory with practice, allowing students to apply their new skills immediately to real-world scenarios. Parents can expect their child to work on a series of projects that build toward a final machine learning application. Projects include controlling LEDs, creating songs with buzzers, motion detection, and more advanced concepts like ultrasonic ranging. The interactive and hands-on approach ensures that students stay engaged and develop both coding and critical thinking skills. By the end of the course, students will not only have a solid foundation in Python and Raspberry Pi but will also understand how to apply machine learning concepts to real-world projects. For a week to week program, check out the syllabus.
학습 목표
Students in our Raspberry Pi course delve into computing, mastering Python for controlling electronic modules and exploring machine learning applications across eight guided projects.From setting up the Raspberry Pi to crafting circuits and programming in Python, they create smart electronic systems integrating machine learning models with input and output devices like LEDs, IR sensors, and servos.
강의 계획서
10 레슨
10 주 이상레슨1:
Setup and Software
The first lesson is dedicated to ensuring all students have set up their Raspberry Pi OS properly, connecting using VNC, and introducing the desktop, command line, and common applications.
Task: Set up and connect to Pi
Finish any set-up steps that could not be completed before class and introduce Raspberry Pi. Ensure students can connect to the Raspberry Pi using VNC without issue. Introduce Linux command line basics and the Thonny Python IDE. 60 분 온라인 라이브 레슨
레슨2:
Hardware and Circuit Basics
Students will test the Raspberry Pi GPIO pins, identify all components necessary for this course, and learn the basics of electricity and safe circuit construction.
Task: Identify components and learn electronics concepts
Ensure students can locate all necessary parts and that GPIO pins are functional before beginning circuit construction lessons. Provide students with an understanding of circuits and electricity with a combination of lesson instruction and short informational videos. 60 분 온라인 라이브 레슨
레슨3:
LED Blink Project
Designed to act as a starter project to introduce proper use of the breadboard, basic hardware components, and programming on the Raspberry Pi.
Task: LED Blink Project
Students will follow along to construct their first circuit and write python code that turns an LED on and off in a loop. 60 분 온라인 라이브 레슨
레슨4:
Machine Learning
Students learn the basics of machine learning and create their own machine learning models that will predict whether the sentiment of some text is happy or sad. The prediction from this model will be used to control the LED circuit.
Task: Machine Learning Setup
Students log in to aicode101.com to create their first model, using Python's requests module to interact with the site's API for predictions, and modify the LED_blink code to control the LED based on these predictions. 60 분 온라인 라이브 레슨
그 외 세부 사항
학부모 가이드
Dear Parents,
Thank you for your interest in our Machine Learning in Python With Raspberry Pi & Sensors program. In this online live course, students will program in Python to control various electronic modules that connect to Raspberry Pi including LEDs, buzzers, servos, ultrasonic sensors, IR sensors, and more using machine learning models. This program is for intermediate to advanced students who had at least 10 hours of Python experience and are new to programming on the Raspberry Pi. This class requires a lot of hands-on experience, and can be quite challenge to some young students. It may also require some involvement from parents, particularly when setting up the Raspberry Pi operating system. Some students are able to complete the setup independently, while others may need assistance with these steps. Please communicate with your learner before enrolling in this class. To prepare, please purchase the hardware listed in the Materials section and Learner Supply List one week before the first class to allow time for shipping.
For our lessons, students will need to install our prepared Raspberry Pi OS image which has been specifically configured for our courses. It contains the necessary files and settings, and has been tested thoroughly with every lesson to ensure everyone can be successful with the projects. Our environment also features a new simplified headless setup method which allows you to enter WiFi settings directly on your Raspberry Pi from any device. We require students to use VNC Viewer to access the Raspberry Pi desktop so that instructors are able to assist with programming. If students prefer to use a separate monitor and keyboard, they may do so in addition to connecting through VNC. To get started, please watch the setup video.
https://www.youtube.com/watch?v=PbAK4gUvZkk
All required software is available on Windows or Mac - No Chromebooks. Please see technical requirements in Sources for more details.
Important notes:
As per Outschool Policy: For the safety of all students, all cameras must be on during the entire class duration, or at least for the first few minutes of the class session in certain circumstances. Please mute your audio (keep video enabled) during the class session.
For those that have never used Outschool before, please follow this link for some awesome preparation before our first class:
https://support.outschool.com/en/articles/802757-how-to-prepare-for-your-first-class
To join the class, please login to your Outschool account and click the scheduled session to get into the classroom, where you click “Join live meeting” to join the zoom classroom. There is no zoom link needed.
If you have any questions/concerns please feel free to reach out through us on Outschool. We are beyond excited to have this opportunity to go on this amazing coding adventure with you all. Please come prepared and ready to learn for our first class, see you soon!
Best regards,
AI Code Academy
사전 요구 사항
At least 15 hours of Python programming experience
Recommended experience: Project-Based Python Level 2 or higher
수업 자료
Prerequisites: Python experience (10 hours at least) required Materials: students need to purchase the following items: 1, Raspberry Pi Kit from: https://a.co/d/fHRuqCH or https://www.canakit.com/raspberry-pi-4-extreme-aluminum-case-kit.html 2, Freenove Ultimate Starter Kit for Raspberry Pi ($49) https://a.co/d/7031zX4 3, If your computer doesn't have a SDHC card port, you also need to purchase an adapter https://www.amazon.com/Vanja-Adapter-Portable-Memory-Reader/dp/B00W02VHM6
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이 수업에서는 아웃스쿨 교실 외에도 다음의 툴을 사용합니다:
출처
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 Chromebooks!!!
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
가입일: April, 2020
4.7
1764수강 후기
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**USE PROMO CODE: CODEAINEWYEAR2025 FOR $25 OFF ANY 10 WEEK COURSE - Valid until Feb 15**
~We offer early registration, sibling discounts, and multi-course bundles. ~
~Check out our complete Outschool offering here: https://shorturl.at/bcBGP ~
~Get to know our coaches here: https://tinyurl.com/5j5crx59 ~
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.
Get to know our coaches here: https://tinyurl.com/5j5crx59리뷰
실시간 그룹 수업
매주
US$26
10주 동안 주당 1회
60분
176 명의 학생이 수업을 완료함
실시간 화상 수업
연령: 11-16
수업당 학습자 5-8 명
