Machine Learning Projects With Scratch Coding (Level 4)
In this 10-lesson online course, students will have hands-on experience training machine learning models to recognize sound, images, and text, and will apply the trained models using Scratch to create impressive projects.
AI Code Academy
Average rating:
4.7
Number of reviews:(1,737)
Popular
What's included
10 live meetings
10 in-class hoursHomework
1 hour per week. Students will create an individual final project of their own design. They can spend as much time as they'd like outside of class, but most do not take more than 1 - 4 hours.Assessment
includedClass Experience
In this online live course, students will have hands-on experience training machine learning models to recognize sound, images, and text. They will apply the trained models using Scratch to create projects such as smart assistants, virtual pets, chatbots, emotion recognition systems, and intelligent maze games. Students will be exposed to two different approaches to intelligent problem solving and gain a solid understanding of the difference between rule-based models and data-based machine learning models. Our projects explain how and why we use machine learning, introduce big data, and demonstrate how these concepts can be applied together to create classification and regression models. We teach children computational programming skills and machine learning concepts through project based lessons. This course consists of 9 guided projects and one final project of the students' own design. Students will be asked to demonstrate their machine learning final project in the last class. Prerequisite: At least 15 hours Scratch coding experience is required Recommended experience: Project-Based Scratch for Kids (Level 2) Check the syllabus for a week to week program.
Learning Goals
Demonstrated skills upon graduation:
Solid understanding of supervised machine learning using labels and sample data
Searching and sorting algorithms in Scratch
Abilities to interpret the machine learning results
Enhanced coding skills with loops, variables, and conditionals
Improved problem-solving skills with problems from the real world
Syllabus
10 Lessons
over 10 WeeksLesson 1:
Introduction to AI and Machine Learning
Students will be introduced to the concept of artificial intelligence.
Topics covered:
○ What is AI?
○ History of AI
○ Examples of AI
○ How do machines learn?
○ Creating image recognition machine learning models
Project: Build a machine learning model to detect whether you play rock, paper, or scissors using image recognition. 60 mins online live lesson
Lesson 2:
Pet Commands with voice recognition
Students will learn to create data-based machine learning models using voice recognition to command animated pets in Scratch.
Topics covered:
○ Creating sound recognition machine learning models
○ Recording voice clips for training data
○ Using Scratch to listen for voice commands
Project: Make an animated pet follow verbal commands and do tricks using a sound recognition machine learning model. 60 mins online live lesson
Lesson 3:
Smart Light
Students will learn to create and apply text recognition machine learning models, and compare machine learning solutions with rule-based solutions.
Topics covered:
○ Creating rule-based text matching models
○ Creating data-based machine learning models
○ Comparison of rule-based and data-based solutions
○ Discussion of applications of machine learning for smart home devices
Project: Create a smart light in Scratch that turns on when a command is given using a text recognition model. 60 mins online live lesson
Lesson 4:
Emotion Recognition
Students create models that can recognize emotions of faces using image recognition.
Topics covered:
○ Creating image recognition models
○ Represent confidence of prediction visually in Scratch
○ Understand the importance of quality training data
Project: Train an image recognition machine learning model to recognize emotions in drawings of faces and use Scratch to display the confidence of results. 60 mins online live lesson
Other Details
Parental Guidance
Dear Parents
Welcome to our Machine Learning With Scratch Coding for Kids. In this online live course, students will have hands-on experiences for training AI machine learning systems and building things with them, by creating projects and games with Scratch using text, image, or sound recognition. All lessons are project based and each lesson contains one fun project. All students will be asked to finish a final project with their own ideas which will be presented on the last day. There will be some quizzes for students to finish at home.
To get started, please create an account at https://aicode101.com, which we will be using both in and out of class for this course.
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 see this article on how to prepare for your 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,
Delaware STEAM Academy
Supply List
Technical Requirements: PC (Windows 10) or Mac (macOS 10.13) or ChromeOS with at least a 2GHz processor and 2GB of RAM (4GB of RAM is recommended). Broadband internet with at least 1.8Mbps download and 900Kbps upload speeds Webcam - Either external or built-in (many laptops have an integrated camera). Microphone and Speakers - We recommend headphones with an integrated microphone
External Resources
In addition to the Outschool classroom, this class uses:
Joined April, 2020
4.7
1737reviews
Popular
Teacher expertise and credentials
Project-based, STEM Coding + AI Programs + Mathematics
Early registration, Sibling and Multi-Course Bundle discounts Available!
The list of our summer camps can be found in this file: https://shorturl.at/bcBGP
AI Code Academy offers the following project-based learning programs:
(1) Basic Computer Skills (Grades 1-8)
(2) Scratch Coding Projects（Grades 2–5） two levels
(3) Micro.bit Coding Projects（Grades 3–4）
(4) AI Machine Learning Projects with Scratch（Grades 4–6）
(5) Roblox（Grades 3–8）Two levels
(6) Project-Based Python for Kids (Grades 4–12）
(7) Game Design with Unity 2D & 3D（Grades 4–12） two levels
(8) Project-Based JavaScript for Kids（Grades 4–12） two levels
(9) Web Design for Kids: HTML & CSS & WordPress （Grades 4–12）
(10) Int./Advanced Python Projects for Kids（Grades 5–12）(two levels)
(11) AI Machine Learning in Python with Raspberry Pi & Sensors（Grades 6–12）three levels
(12) AI Machine Learning in Python with Big Data（Grades 6–12）
(13) Machine Learning in Python with Raspberry Pi & Smart Devices (Grades 6–12
(14) Project-Based Java（Grades 6–12）
(15) Project-Based C++（Grades 6–12）
(16) AP Computer Science A (grades 9-12)
All of our coaches are college students and/or recent graduates majored in Engineering or Computer Science.
We aim to create effective support for young people to have a successful pathway into careers in science, computer science, engineering, math and artificial intelligence, to challenge gifted minds to learn while doing, and to better prepare our young generation to face an increasingly challenging and complex society in the world of artificial intelligence (AI), big data and Internet of Things (IoT)
We are among the very few organizations who are able to offer AI Machine Learning projects for kids.Reviews
Live Group Course
$209
for 10 classes1x per week, 10 weeks
60 min
Completed by 293 learners
Live video meetings
Ages: 9-11
4-8 learners per class
