Raspberry Pi와 스마트 로봇 자동차를 이용한 파이썬 머신 러닝(레벨 3)
이 고급 과정에서는 학생들은 Python과 Raspberry Pi를 사용하여 머신 러닝과 로봇 공학을 탐구하고, LED 매트릭스와 스마트 로봇 자동차와 같은 실습 프로젝트를 수행하여 코딩 및 전자 기술을 심화합니다.
AI Code Academy
평균 평점:
4.7
수강 후기 수:(1,748)
인기 수업
무엇이 포함되어 있나요?
10개의 라이브 미팅
수업 10 시간프로젝트
주당 2-4시간. Projects are not mandatory but we strongly encourage students to complete them.학습 평가
포함됨수료증
수업 종료 후 1회보고계신 지문은 자동 번역 되었습니다
수업 소개
**USE PROMO CODE: CODEAICODEOFF30 FOR $30 OFF ANY 10 WEEK COURSE - Valid until Dec, 27 , 2024** In this advanced 10-lesson course students will explore the fascinating world of machine learning and robotics. Starting with integrated circuits and advanced circuit designs, they will work on exciting projects like controlling LED matrices to display images and numbers, building a 4-digit counter using a 7-segment display, and integrating attitude sensors with DC motors. Throughout the course, students will learn how to implement matrix keypads for stepper motors and combine various sensors and components to control robotic systems. By the end, they will have the skills to build and program their own smart robotic car, capable of performing complex tasks. For a week to week program, check out the syllabus.
학습 목표
Students will learn how to control and communicate with various sensors using Python coding and Raspberry Pi and smart car
강의 계획서
10 레슨
10 주 이상레슨1:
LED Matrix
Provide students with an advanced example of integrated circuit usage, as well as exposure to more complex circuit designs.
Task: LED Matrix Implementation
Aid students in creating the project circuit and code to cycle through an image, numbers, and letters on an LED matrix. 60 분 온라인 라이브 레슨
레슨2:
4 x 7-Segment Display
Designed to provide students with more exposure to integrated circuits, along with a brief introduction to transistors.
Task: 4-Digit Counter
Assist students in the creation of the project circuit and development of code to make an upward-counting display. 60 분 온라인 라이브 레슨
레슨3:
DC Motor
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 60 분 온라인 라이브 레슨
레슨4:
Stepper Motor
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 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 & Robot Car (level 3). This class has a lot of fun hardware and coding projects, from which students have opportunities to learn some fundamental knowledge of both modern machine learning and Internet of Things (IoT). In this course students will learn additional sensors and have an opportunity to assemble and control a robot car using both rule-based and AI based models.
This class requires a lot of hands-on experience, and can be quite challenge to some young students. It also requires a lot of involvement from parents, in particular, to assemble the robot car before class.
Besides the hardware you got in the level 1 course, you would need to purchase Freenove 4WD Smart Car for Raspberry Pi ($69) from this link: https://a.co/d/h6sOKWn.
and two 18650 batteries (or 4) and a battery Charger:
https://www.18650batterystore.com/collections/samsung-18650-batteries/products/samsung-20s
https://www.18650batterystore.com/products/nitecore-i2-charger?_pos=1&_sid=63a69d299&_ss=r
Once you get the smart car kit, please follow the instruction in YouTube to assemble your smart car before your classes. https://youtu.be/vKE2TnTQcG0
Look forward to working with you
All the best
AI Code Academy
사전 요구 사항
20 hours Python experience and 10 hours Raspberry Pi experience or having taken our Raspberry Pi level 1 and two course.
수업 자료
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 iPads and 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
Outschool 외 필요 앱/웹사이트
아웃스쿨 사이트의 기능 외 별도의 앱이나 웹 사이트를 사용할 필요가 없습니다.
출처
Prerequisites: Python experience (15 hours at least) and Raspberry Pi experience (10 hours at least) required
Materials needed: we presume you already had the Raspberry Pi. Please purchase the following smart car
1, AICode101 4WD Smart Car for Raspberry Pi ($99) https://www.illum.ai/products/aicode101-4wd-smart-car-kit-for-raspberri-pi.html
가입일: April, 2020
4.7
1748수강 후기
인기 수업
교사 전문성 및 자격증
**USE PROMO CODE: CODEAICODEOFF30 FOR $30 OFF ANY 10 WEEK COURSE - Valid until Dec, 27 **
~We offer early registration, sibling discounts, and multi-course bundles. ~
~Check out our complete Outschool offering here: https://shorturl.at/bcBGP ~
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
매주
US$30
또는 10 회 수업에US$29910주 동안 주당 1회
60분
17 명의 학생이 수업을 완료함
실시간 화상 수업
연령: 11-15
수업당 학습자 3-8 명
