[ Coding ]
Python for kids
Start with variables, make decisions with if/else, and use loops to solve small coding challenges.
- Print, variables, and types
- Decisions with if and else
- Loops and debugging
[ OPEN LEARNING ] Full lessons, worked examples, and projects are free to read.See the courses
[ FOUNDATIONS → FRONTIER ENGINEERING ]
Big ideas.
Small steps.
Made by you.
Start with Python, AI, and the web. Then go deeper into AI engineering, ML math, systems, inference, and research. Read complete lessons at your own pace.
Free lessons and practice · Sign-in optional
YOUR FIRST BUILD STARTS HERE01 / 03
08Open courses
24Complete lessons
Your paceLearn in small steps
FreeNo sign-in to read
[ THE OPEN COURSE COLLECTION ]
Pick a path. Make it yours.
Choose a subject, read the full lessons, test yourself, and apply what you learn in a small project.
[ Artificial intelligence ]
AI literacy for kids
Explore training data, recognise unreliable answers, and practise thoughtful, responsible use of AI.
- Patterns and training examples
- Bias and checking claims
- Prompts that support learning
[ Web development ]
Web development for kids
Learn how HTML gives a page structure, CSS adds style, and JavaScript makes it respond.
- Content with HTML
- Style with CSS
- Behaviour and accessible design
[ AI engineering ]
AI engineering foundations
Build a small AI feature, test its answers, and understand what it takes to make it reliable.
- From demo to task
- Ground answers in evidence
- Evaluate before shipping
[ ML mathematics ]
Math for machine learning
Read vectors, gradients, and probability as tools for explaining how a model learns.
- Vectors and shapes
- Gradients and learning
- Probability and uncertainty
[ Software systems ]
System design studio
Reason through traffic, queues, caching, and failure with small real-world design cases.
- Start with constraints
- Store, cache, or queue
- Design for failure
[ Model serving ]
Inference engineering
Understand tokens, KV caches, batching, latency, and the trade-offs behind model serving.
- Follow one request
- Memory and batching
- Measure the service
[ AI research ]
Read an AI research paper
Move from a headline to the paper’s claim, method, evidence, and limits.
- Find the central claim
- Inspect the evidence
- Write a useful research note
[ HOW LEARNING HAPPENS ]
Understand it.
Try it.
Make it stick.
01
Find your starting point
A short skill check helps you see what you already understand and what to explore next.
02
Make mistakes useful
Get a hint, understand the answer, then return to the questions that need another look.
03
Build your own rhythm
Set a daily question goal and track your practice on this device, one small session at a time.
What will this little loop do?
for step in range(3):
print("I can build this!")Reveal the idea +
It prints “I can build this!” three times. range(3) gives the values 0, 1, and 2: one repeat for each value.
[ KEEP THE CURIOSITY GOING ]
There’s more than one way in.
01
Learning guides
Read an example, try a small exercise, and bring your questions back to practice.
02Your learning space
Sign in if you want the separate account lessons and saved account progress.
03AI Radar
See what is changing in AI, then follow the original source to understand it.
For curious learners of every age
Beginner lessons and the practice lab work well for younger learners; advanced tracks are designed for readers with the stated prerequisites. The public Learning Lab stores progress in this browser. Every open course stays readable without an account.
[ A LITTLE CLARITY ]
Before your
first chapter.
What is AI Ka School?
AI Ka School is an online learning app for students ages 8–17 to explore coding and artificial intelligence. Its public resources include beginner course overviews, step-by-step guides, and a Learning Lab with practice questions.
Can a complete beginner start here?
Yes. Start with Python variables, AI literacy, or HTML basics. The public guides explain the terms and include worked examples. Younger learners may find it helpful to work alongside a parent or teacher.
Can I try practice without creating an account?
Yes. The Learning Lab and public guides are available without signing in. The lab offers short practice sessions, explanations, and review questions. Create an account separately to explore the account-based learning experience.
How is the Learning Lab different from account lessons?
The Learning Lab is a self-contained practice space for Python, AI literacy, and web basics. Its practice progress is stored in this browser and does not update account XP or lesson completion. The course overviews describe learning topics; available account paths are shown after signing in.
Does Learning Lab progress sync between devices?
No. Learning Lab progress stays in the browser you use. Clearing site data, changing browsers, or using another device may remove or separate that progress. It is not linked to your AI Ka School account.
Do I need to install software?
You can read the guides and answer Learning Lab questions in a browser. The optional Python projects need a Python environment, and the web page guide uses a text editor and browser. Public practice questions do not execute Python programs.
How should students use AI while learning?
Try the problem first, ask for a hint, and explain the answer in your own words. Verify factual claims with an original source or a small test. Use fictional examples and avoid sharing private information in prompts.
Which topic should I choose first?
Choose Python if you enjoy logic and solving puzzles, web development if you want to create pages, or AI literacy if you want to understand predictions and check AI answers. Try a short practice session, then use your mistakes to decide what to review.