サマーキャンプ: Scratch コーディングによる機械学習プロジェクト (レベル 4)

 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. 

 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. 

 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. 

 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.