Classes 8-10

Young AI Engineer

“I can build and deploy AI applications.”

Your child works like a real developer: GitHub profile, five real projects, and at least one deployed AI application.

The capstoneDeploy My First Production AI ApplicationAnswers in their subject, with the prompt they wrote behind it.

How the year runs

Length: 16 weeks
Live sessions: 32, with a mentor
Marked work: Practicals, with written feedback
Ends with: Deploy My First Production AI Application
Parents see: Attendance, marks and feedback

Fees for the year₹14,999

Enrol for the year Meet a mentor first

An Alpha Plus plan for your child's class already opens this program's self-paced material. Enrolling adds the live part. What a year costs

The outcome

What your child walks out with

5 finished pieces of work, built one at a time and reviewed by a mentor. Not exercises: things that run, that they can open and show you.

01AI Quiz GeneratorWrites questions, marks answers, and explains the wrong ones.

02AI Study AssistantAnswers in their subject, with the prompt they wrote behind it.

03Document Q&AReads a document they upload and answers only from it.

04Personal AI TutorAnswers in their subject, with the prompt they wrote behind it.

05Full-stack AI ApplicationA front end, an API and a database, deployed and reachable.

Screens are drawn to show the shape of each build, not one student's work. Finished projects live in your child's own portfolio, which you can open from the parent dashboard.

Curriculum

What gets taught, module by module

10 modules, across 32 live sessions. Concepts are introduced when a project needs them.

Developer Setup4 topics

Files, folders and terminal
VS Code
Python and packages
Virtual environments

Python Engineering4 topics

Functions, modules and packages
Error handling
OOP fundamentals
Clean coding basics

Git & GitHub4 topics

Repositories
Commit, push, pull
Branches concept
README and documentation

Internet & APIs4 topics

HTTP and HTTPS
Requests, responses, methods, status codes
REST
JSON

Backend4 topics

FastAPI
Endpoints
Validation
Basic authentication concepts

Databases4 topics

Relational data
Basic SQL
CRUD
Managed databases

Modern AI5 topics

LLM concepts, tokens and context
Prompting and system instructions
AI APIs
Structured output
Multimodal concepts

AI Engineering4 topics

Embeddings and semantic search concepts
Vector database concept
Basic RAG
Document Q&A

Product Integration1 topic

Frontend + backend + AI + database

Deployment3 topics

Environment variables
Deploy from GitHub
Logs and basic debugging

Week by week

What the time actually looks like

16 weeks, about 3.3 hours a week: 1.5 with a mentor, 0.9 of guided material and 0.9 of their own project time.

With a mentor: 24h; over 16 weeks
Guided material: 14.8h; over 16 weeks
Their own project time: 14.3h; over 16 weeks

Week by week, all 16 weeks

Week	Focus	Mentor	Guided	Own work
1	Readiness check, and setting up a real environment	90m	60m	30m
2	Git: saving work you can go back to	90m	60m	40m
3	Structuring an application rather than a script	90m	60m	45m
4	Modules, imports and where things belong	90m	60m	45m
5	Calling an API and handling what comes back	90m	60m	50m
6	Storing data so it survives a restart	90m	60m	50m
7	An interface somebody else can use	90m	60m	50m
8	Validating input you did not write	90m	60m	50m
9	Grounding an answer in a source	90m	60m	60m
10	Building the feature	90m	60m	70m
11	Evaluating it: what does good look like	90m	60m	70m
12	Measuring it honestly, including the failures	90m	60m	70m
13	Deployment, and what breaks in the open	90m	45m	60m
14	Reliability: retries, limits and logging	90m	45m	60m
15	Reviewing somebody else's work	90m	45m	60m
16	Presenting the system and its limits	90m	30m	50m

What gets marked

3 assessed pieces of work. Everything else is practice.

A structured application under version controlweek 8

The history shows work in steps, not one commit
Input from outside the program is validated
Another learner can run it from the repository alone

A grounded feature with an evaluationweek 12

Answers cite the source they came from
There is a measured result, not an impression
A failure case is documented rather than hidden

The deployed system and its presentationweek 16

It runs somewhere other than the author's machine
Limits and costs are stated
The learner answers a question they did not prepare for

Optional extras: A second data source for the same feature, A dashboard for the evaluation results, Reviewing a peer's repository against the same criteria

How it is marked

Automatic checks, AI suggestions and a mentor's decision are recorded separately, and a mark can be revised after feedback or appealed.

Functionality and accuracy35%
Reasoning30%
Testing and iteration20%
Communication and responsible use15%

How marking works is the same across every program.

Before week one

Checked before week 1. A learner who does not pass is offered Coding & AI Builder first rather than being enrolled and left behind.

What is checked

Write a short Python program using a loop and a function
Read an error message and locate the line that caused it

Assumes your child can already write and debug a small Python program. If not, Coding & AI Builder covers that first.

Before you enrol

What your child needs

Said up front, because a laptop requirement discovered in week three is too late to discover it.

Prior knowledge

Some coding exposure helps; ambitious beginners are welcome.

Equipment

Windows/macOS/Linux laptop
8GB RAM recommended
VS Code + Python (guided setup)
Modern browser

Tools they will use

VS CodePythonGitGitHubPostmanFastAPIAI APIsSupabaseVercel / Render

Every program runs the same way — learn it, build it, get it marked, with what you see as a parent the same throughout.

Where this goes

One year of nine, and it is built to continue

Alpha Euron runs from Class 4 to Class 12. Each program assumes what the one before it taught and hands over to the one after it, so a child who starts in Class 4 finishes school having built for nine years rather than having taken nine unrelated courses.

After Young AI Engineer, the natural next step is Agentic AI Builder, which opens with build AI systems that search, reason, remember and use tools.

What they keep when it ends

A portfolio that is theirs

Every reviewed build stays in their account, openable and shareable, after the year ends.

A certificate that can be checked

Issued on completion with a number anyone can verify on this site, without a login.

Demo Day, in front of people

They present the capstone and answer questions on it. Most children have never done that.

The next year, already mapped

Each program ends where the next one starts, so nothing is repeated and nothing is skipped.

Questions

Before you enrol

Is this the right class for my child?

This program is designed for Classes 8-10. If your child is outside that range, or you are unsure, Find the Right Program recommends exactly one, and the free class confirms the fit.

What happens if they miss a class?

Lessons and guided practice stay available in the platform, and mentors help students catch up in the next session.

What equipment is needed?

A regular laptop with a browser is enough to start. Mentors help with any setup in class.

How are projects reviewed?

A mentor reviews every submitted project with marks and written feedback. Students can improve and resubmit.

Is this included in an Alpha Plus plan?

Partly. A plan for your child's class already opens this program's self-paced material. Enrolling adds the live part: scheduled sessions with a mentor, marked practicals and Demo Day.

Ready when your child is

The first class is free and includes a small hands-on project. Enrol whenever you are ready; the price is ₹14,999 for the whole program.

Enrol in Young AI Engineer Book a free class