Advanced level, ages 15–17: Python programming, machine learning, web development and data science
Teenagers write clean Python, analyse real data, build web pages and learn how machine learning and generative AI work, the way professionals do: plan, build, test and improve. They finish with an AI-powered study tool or a recommendation app for their portfolio.
At a glance
- Who it is for
- Students aged 15–17 (Classes 10–12)
- Suggested practice
- About 2 hours a week
- Before you start
- Comfort with a computer; basic Python helps but is reviewed in the first weeks.
- Covers
- Python programming, Data science basics, Machine learning fundamentals, Generative AI, Web development, AI ethics
What you get
- Short video lessons with notes, resumable on any device
- Coding exercises that run and check themselves in the browser
- Quizzes, weekly projects and a final project reviewed by a teacher
- Progress for parents and a verifiable certificate
What your child will learn
- Python programming: functions, modules, files, error handling and simple tests.
- Data science basics: cleaning data, averages, trends and charts.
- AI and machine learning fundamentals: classification, training and test data, accuracy and overfitting.
- Generative AI: how language models produce text, why they can be wrong, and responsible use.
- Web development: HTML, CSS and a little JavaScript for an interactive page.
- Software design, cybersecurity basics and AI ethics.
Week-by-week plan
The order can change slightly between batches, and every week ends with a hands-on activity.
| Week | Topic | What students do |
|---|---|---|
| 1 | Python refresh and good habits | Functions, modules and reading error messages |
| 2 | Files, errors and tests | Save and load data; handle errors; write simple tests |
| 3 | Designing software | Plan an app with user stories and pseudocode |
| 4 | APIs and JSON | Read JSON from a public API; keep keys out of shared code |
| 5 | Data analysis | Clean a dataset and find trends with charts |
| 6 | Machine learning concepts | Classification, training and test data, accuracy |
| 7 | Build a simple model | Train and evaluate a small classifier |
| 8 | Generative AI | How language models work, hallucinations and responsible use |
| 9 | Web apps | Build a small web app with a form, logic and output |
| 10 | Cybersecurity basics | Passwords, phishing, input validation and privacy by design |
| 11 | Ethics and user testing | Check for bias, test with users and improve |
| 12 | Final project and demo day | Present an AI-powered study tool or recommendation app prototype |
Final project: an AI-powered study tool or recommendation app prototype
Students plan, build and test a working prototype, such as a revision-question generator with answer checking, a study planner, or a book or activity recommender built from a small dataset. They present it on demo day with a short design and ethics review.
- A clear problem, users and plan
- Working code split into functions or modules, with basic tests
- Use of data, an API or a simple model
- An honest review of limits, bias, privacy and security
How the course runs
- 12 weeks, one or two lessons a week of about 60–75 minutes.
- Python exercises run in the browser; students may also use Python on their own computer for bigger projects.
- Weekly exercises, quizzes and rubric-based project reviews.
- Live batches add code reviews, debugging clinics and the demo day.
Skills that last
Engineering habits
Planning, testing and improving software instead of writing it in one go.
AI-ready future
Knowing what models can and cannot do, useful in every career.
Portfolio
A finished project for exhibitions, competitions and college applications.
The course
Included in the ₹365 yearly plan. Open it to see every lesson and try the free ones.
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Book a free demo class with a teacher
Tell us your child’s class and we will call to fix a time. The teacher also checks which level suits your child.
Frequently asked questions
Does my child need to know Python already?
It helps but is not required. The first two weeks review the basics, and the free demo includes a short Python exercise to check comfort.
Does it help with Class 11–12 Computer Science?
The Python and data topics overlap with many Computer Science and AI syllabuses, but the course is project-based. Use your school syllabus for exam preparation.
Are paid AI services or API keys needed?
No. Everything runs with free tools in the browser. Students learn why keys and personal data must never go into code they share.