Products

Elementary | Middle
CodeHop Standards aligned coding for districts Tynker Gamified coding and apps Typing Easy to use typing for schools

Middle | High
CodeHS Pro Comprehensive CS platform Certifications Industry based credentials for CTE

AI
AI Creator Easily create lessons with AI Bool AI coding and prototyping
Products Explore what CodeHS has to offer for districts, schools, and teachers
- Elementary | Middle
- CodeHopStandards aligned coding for districts
- TynkerGamified coding and apps
- TypingEasy to use typing for schools
- Middle | High
- CodeHS ProComprehensive CS platform
- CertificationsIndustry based credentials for CTE
- AI
- AI CreatorEasily create lessons with AI
- BoolAI coding and prototyping
- Use Cases
- DistrictsComprehensive solutions for districts
- SchoolsTools and resources for schools
- TeachersEmpower educators in the classroom
Platform
Platform
Curriculum
Computer Science Curriculum

Customizable K-12 Computer Science Curriculum
Overview
Curriculum Customizable K-12 Computer Science Curriculum
Professional DevelopmentPD
Professional Development

Online & In-Person Training for Teachers
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Professional Development Online & In-Person Training for Teachers
Online IDE
Online IDE

Write, Run, & Debug Code in an Online IDE
Overview ›
- JavaScript
- Python
- Java
- HTML
- C++
- SQL
Online IDE Write, Run, & Debug Code in an Online IDE
- Online IDE
- JavaScript
- Python
- Java
- HTML
- C++
- SQL
- Karel
Resources
Resources

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CodeHS Glossary

K-means General

An iterative clustering algorithm that uses an expectation-maximization approach to separate the data into clusters