CodingChamp

Courses

Grade 8-12

Student in a CodingChamp Python class
Grade 5-7 / Grade 8-12

Python

Python is one of the most widely used and in-demand languages, prized for its simple, readable syntax. Students learn conditional statements, looping constructs, classes and objects, then apply their learning to build GUI programs with Tkinter and real-world mini projects — a foundation for later work in Data Science, Machine Learning, and AI.

  • Conditionals, loops, classes & objects
  • GUI programs using the Tkinter library
  • A foundation for Data Science, ML & AI
Student in a CodingChamp Video Editing (Premiere Pro) class
Grade 8-12 / Grade 5-7

Video Editing (Premiere Pro)

A hands-on Premiere Pro CC curriculum — from understanding the workspace and timeline through trims, transitions, titles, audio, and color correction — building up to full creative projects like a music video and a short movie.

  • Timeline editing, transitions, titles & audio
  • Color correction with the Lumetri panel
  • Capstone projects: a music video and a short movie
Student in a CodingChamp Photoshop & Graphic Design class
Grade 8-12 / Grade 5-7

Photoshop & Graphic Design

Adobe Photoshop is the predominant photo editing and manipulation tool on the market. Students learn its fundamentals and graphics concepts, working up through retouching, layers, masks, and filters to real design projects — posters, business cards, and full website UI mockups.

  • Retouching, layers, masks & filters
  • Real projects: posters, business cards, website UI
  • Complete understanding of Photoshop & design concepts
Grade 5-7 / Grade 8-12

AI & Machine Learning for Kids

A hands-on introduction to artificial intelligence and machine learning, built on the Python foundation from our other courses. Students explore how AI actually works — training simple image and text classifiers, experimenting with tools like Google's Teachable Machine, and building beginner chatbots — while learning to think critically about how AI is used (and misused) in the real world.

  • How machine learning models are trained, in plain language
  • Hands-on projects: image classifiers, simple chatbots
  • AI ethics — bias, privacy, and responsible use