Best AI Courses for Kids: 10 Platforms Compared by Age

Under about age 10, the right AI course for a child is usually no paid course at all: Google Teachable Machine and Machine Learning for Kids are free and cover what a young child needs. From roughly age 10, a structured multi-year curriculum starts to earn its price. From 15, ordinary adult courses like Coursera's AI For Everyone are the better buy, and the "for kids" label stops meaning much.

Ten platforms are compared below on age range, price, free tier and what you actually get for the money, followed by a straight age-to-platform lookup.

Much of what is sold as an "AI course for kids" is really a chatbot-prompting tutorial, or a coding course with an AI unit bolted on. The entries below separate what you are buying from what the landing page claims.

This page is for choosing what to buy. If you want to understand AI yourself first — what it is, what a child should grasp at each stage and how to talk about it at home — read the complete guide to AI for kids instead and come back here when you are ready to compare prices. Teachers evaluating this for a classroom rather than one child should start with the K-12 AI education guide. And if the reason you are here is that you would rather a child's work never left the house at all, the local AI privacy guide explains what that actually buys you — and what it does not.

What does each platform cost, and what do you get?

1. LittleAIMaster — structured Grades 6-12 curriculum

What you are buying: almost every other entry here is a single course, a single tool, or an AI unit inside a computer science curriculum. This one is sequenced across seven school years, so Grade 9 assumes Grade 8. Per its published outline, concepts and data come first in Grades 6-7, Python arrives in Grade 8, machine learning and neural networks in Grades 9-10, and LLMs and generative AI in Grades 11-12.

Pros:

• Multi-year progression rather than isolated projects
• No coding required until Grade 8, so a 10-year-old can start
• Web, iOS and Android, per its own download links
• Parent and teacher dashboards for progress tracking
• Described on its own site as "COPPA-aligned" and "designed to meet COPPA standards"

Cons:

• Most of the content sits behind a subscription; the free sample is only 3 chapters
• Less hands-on coding than tool-first platforms like App Inventor
• Far newer and less battle-tested in schools than Code.org or Khan Academy
• Text-and-quiz format suits self-motivated readers; reluctant readers will prefer video

Best for: parents who want one thing a child can stay on for years, and who will judge it on the free chapters before paying.

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2. Google Teachable Machine — free, ten minutes, no account

What you get: a free browser tool from Google that lets a child train an image, sound or pose classifier through a webcam. No account, no install, no code. Start at teachablemachine.withgoogle.com.

Pros:

• Completely free, no sign-up
• A working model in minutes, on any device with a browser
• Makes "training data" concrete faster than anything else on this list

Cons:

• A tool, not a curriculum — no progression, no tracking
• Limited to image, sound and pose classification
• A child will exhaust it in an afternoon

Best for: the first hour, before you spend anything.

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3. Machine Learning for Kids — free, ages 8-12

What you get: a free site at machinelearningforkids.co.uk that bolts machine learning onto Scratch. Children train a text, image or number classifier, then use it inside an ordinary Scratch project.

Pros:

• Free
• Builds on Scratch, which most children already meet at school
• Project-based, so the AI does something visible
• Workable for 8-year-olds with an adult nearby

Cons:

• Setup needs an adult (API keys and accounts for some project types)
• Shallow compared with a full curriculum
• Scratch itself starts to feel limiting around age 12

Best for: primary-age children who already use Scratch.

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4. MIT App Inventor — free, builds real Android apps

What you get: MIT's visual app builder at appinventor.mit.edu, with extensions for image classification, chatbots and other AI features.

Pros:

• The output is a real, installable app — a strong motivator for teens
• Free, with a large community and published teaching materials
• Backed by MIT, so the materials are stable and well documented

Cons:

• The subject is app development; AI is an add-on
• Steeper learning curve than block-only tools
• Android-oriented output

Best for: teens who want to ship something, not study something.

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5. Coursera AI For Everyone — an adult course teens can follow

What you get: Andrew Ng's non-technical AI For Everyone course. Because this gets misreported: there is no children's edition. It is an adult course with no maths and no coding, which is why able 15-plus students can follow it. Free to audit; you pay only for the certificate.

Pros:

• High-quality material from a leading practitioner
• Free to audit, so the trial costs nothing
• Strong on what AI is actually used for

Cons:

• Written for working adults — dry for under-15s
• Not hands-on at all
• No child accounts or parent controls

Best for: mature 15-18s who want the strategic picture rather than the code.

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6. Code.org AI modules — free, built for classrooms

What you get: AI units inside Code.org's wider computer science curriculum, free and already installed in a huge number of schools.

Pros:

• Free, with teacher accounts, rosters and lesson plans
• Slots into a CS course a school is probably already running
• The most established option here for classroom use

Cons:

• AI is a small slice of a broader curriculum
• Less depth than a dedicated AI platform
• Paced for a class, which can frustrate a fast learner at home

Best for: schools, and any parent whose budget is zero.

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7. Khan Academy AI content — free, maths-led

What you get: a growing set of AI-related material inside Khan Academy's free platform, tied to the maths it already teaches well.

Pros:

• Free, self-paced, trusted by parents and schools
• Connects AI to maths a child is already studying
• Strong progress tracking

Cons:

• The AI material is still being built out
• Primarily video-led
• Not a coherent AI course yet

Best for: students who want the maths behind AI rather than the tooling.

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8. AI4K12 — a free framework, not a course

What you get: AI4K12 is not something you enrol a child in. It is the "Five Big Ideas" framework, grade-band progression charts and curated resource list produced by AI educators for K-12, and it is the yardstick used in this comparison.

Pros:

• Written by AI education specialists
• Free
• The best free tool for a parent or teacher assembling their own programme

Cons:

• Requires an adult to assemble it into lessons
• No student experience, no tracking
• Linked third-party resources vary in quality

Best for: teachers, curriculum planners, and parents who want to sanity-check a paid platform's claims.

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9. CodaKid — paid Python and game courses with mentors

What you get: project-based courses at codakid.com teaching Python and basic ML through game and app building, with human mentor support.

Pros:

• Tangible outcomes children want to show people
• Real coding skill, not just AI vocabulary
• Mentor support is available, which few platforms offer

Cons:

• Heavily weighted towards coding; AI concepts are thin
• Paid subscription, and the most expensive style of option here
• Smaller library than the free giants

Best for: children who want to learn Python and treat AI as one thing you can build with it.

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10. Brilliant — paid interactive maths and ML puzzles

What you get: interactive problem-solving courses at brilliant.org covering machine learning through puzzles rather than lectures.

Pros:

• Outstanding for maths-inclined students
• Interactive rather than passive
• Good mobile app for short daily sessions

Cons:

• Built for adults, not children
• Too demanding for most under-14s
• Little practical application — you will not build anything

Best for: maths-strong 14-18s interested in how the models actually work.

Side by side:

Prices move, and vendor pricing pages are the only reliable source — each platform above links to its own.

Which one fits your child's age?

Age is the decision, so here it is as a lookup:

Four things worth knowing before you commit money:

1. Start from where the child is, not their year group. A 12-year-old who has never coded belongs in the 10-12 row regardless of school year.
2. Free first, always. Teachable Machine and Machine Learning for Kids cost nothing and will tell you within two weekends whether the interest is real. Paying before that is how subscriptions get abandoned in month two.
3. Match the format to the child. Reluctant readers stall on text-and-quiz curricula no matter how good the content is; App Inventor or Teachable Machine is the better spend for them.
4. Buy in years, not weeks. An annual plan on a platform with real progression beats three monthly subscriptions abandoned in turn — but only after the free stage has proved the interest.

What do parents ask before paying?

What is the best AI course for a child? There is no single answer, and any list that gives you one is selling something — this one included, since the platform at number one belongs to the owner of this site. Under 10, free tools beat paid courses outright. From 10, a structured curriculum with real progression is worth paying for. From 15, adult courses are usually the better buy.

Which AI courses for kids are genuinely free? Four here cost nothing at all: Google Teachable Machine (no account needed), Machine Learning for Kids, Code.org's AI modules including teacher accounts, and Khan Academy's AI content. Between them they cover most of what a child under 13 needs, and none of them are stripped trials. LittleAIMaster — again, same owner as this site — opens its first 3 chapters without a card, which is a sample rather than a free tier.

How much should this cost? Anywhere from nothing to roughly $25 a month depending on the platform. Check each vendor's current pricing page; the free options above are enough for most primary-age children.

What does a school licence cost? Schools need what parents do not: rosters, a teacher dashboard, curriculum alignment and per-seat billing. Code.org remains the strongest free answer. For paid per-seat licensing, LittleAIMaster's school edition — owned by the same person who owns this site — publishes $45 per student per year at 30-99 seats, $36 at 100-499, and $30 at 500-1,999, with custom pricing above that, which is roughly $2.50 to $3.75 per student per month at those tiers. Teacher portal access is included, and its site notes that final pricing is negotiated through regional partners. Ask any vendor for a written quote before budgeting, and see our K-12 AI education guide for how districts sequence this alongside existing CS courses.

What should you check before paying? A free sample you can judge without a card, a published price rather than "contact us", a stated position on under-13 data handling, a parent or teacher dashboard, and whether the course puts a child in front of a live chatbot at all.

Can a child learn at their own pace? Almost all of these are self-paced, which is what makes them workable for homeschoolers and for children with full schedules. Code.org is the exception when a school runs it to a class timetable.

The honest summary: spend nothing for the first month, use Teachable Machine and Machine Learning for Kids to find out whether your child actually enjoys this, and only then buy a structured curriculum — from the owner's other site or from anyone else on this list. No subscription bought in week one has ever created interest that was not already there.

Buying for yourself rather than for a child? Our own AI learning path for adults is a separate catalogue on this site, and nothing on this page is required to use it.