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6 months (weekend batches) \u00b7 hybrid

AI for Students — Real AI Skills for Class 9-12

Real AI for school students aged 14-18: prompt engineering, Python ML, ethical AI use, and portfolio projects. Designed by AI practitioners, not generalist teachers.

Duration
6 months (weekend batches)
Mode
hybrid
Fees
\u20b925K

Why AI literacy is now a baseline skill

In 2026, the question isn’t whether your child should learn AI\u2014it’s whether they should learn it now or two years late.

Every career your child will pursue will involve AI. Whether they become engineers, doctors, designers, lawyers, researchers, or entrepreneurs\u2014AI will be a baseline tool, the way Excel is a baseline tool today. Students who learn AI now will be 5\u201310 years ahead of their peers in college, internships, and the careers that follow.

But the AI literacy market is full of noise. “Kids coding” classes that teach Scratch and call it AI. “AI summer camps” that show kids ChatGPT prompts. Online courses that bury 14-year-olds in math-heavy theory before they’ve built anything.

Our AI for Students program is different because it’s designed by people who actually build with AI for a living\u2014not generalist teachers re-skinning a coding class as “AI.”

What students actually learn

The 6-month program covers four progressive skill layers:

Layer 1: AI literacy. What AI is, how LLMs work, where the limits are, how to use AI responsibly. This isn’t optional theory\u2014it’s the foundation that prevents students from being intimidated by hype or fooled by hallucinations.

Layer 2: Prompt engineering. How to get genuinely useful work out of AI tools. Chain-of-thought, few-shot examples, building workflows. Most adults don’t use AI tools well; we teach 14-year-olds to use them as power users.

Layer 3: Python and ML basics. Real Python\u2014not block-based or simplified versions. Students learn to manipulate data with pandas, visualize it with matplotlib, build their first machine learning models with scikit-learn. By month 4, they’re comfortable with code.

Layer 4: Building AI applications. Calling Claude or OpenAI APIs from Python. Building chatbots, summarizers, classifiers. The final two weeks are a portfolio project where each student ships something real.

Why this matters for college and career

Three concrete advantages our students walk away with:

  1. A portfolio of 5-7 real AI projects they can show in college applications, internships, and conversations. This puts them in the top 1% of high schoolers globally.

  2. Foundation for advanced college programs. Students entering CS, data science, or engineering programs at college level skip 1-2 years of foundational catch-up.

  3. Future-proofing. AI skills compound. Students who start now have built mental models that will let them learn whatever new AI techniques emerge in 2027, 2028, 2030.

How the class works

Format: Hybrid \u2014 some sessions in-person at Wakad campus, some online via live Zoom (for flexibility around boards/exam schedules).

Schedule: Weekend batches only. Saturday + Sunday, 2-hour sessions. Morning or evening batches available.

Batch size: Capped at 20 students for hands-on attention.

Faculty: Led by AI practitioners with experience building production AI systems. Not generalists.

Tools: Google Colab (free), Python, scikit-learn, Claude/OpenAI APIs (we provide credits for the program).

Apply for the next batch

AI for Students batches start every 3 months. Next intake details and schedule available via WhatsApp\u2014reach out to discuss your child’s grade level, prior experience, and the right batch fit. Seats fill quickly given 20-student limit.

Curriculum

What students will learn.

  1. 01 AI Fundamentals (4 weeks)
    • What is AI — history, present, and where it's going
    • How LLMs (ChatGPT, Claude, Gemini) actually work
    • Difference between AI, ML, deep learning
    • Real-world AI applications across industries
    • Ethical AI — bias, hallucination, responsible use
  2. 02 Prompt Engineering Mastery (4 weeks)
    • Foundations of effective prompting
    • Chain-of-thought, few-shot, zero-shot techniques
    • Building AI workflows for academic research
    • Using AI for writing, coding, problem-solving
    • Hands-on projects with ChatGPT, Claude, Gemini
  3. 03 Python for AI (8 weeks)
    • Python basics — variables, control flow, functions
    • Working with data (lists, dicts, pandas basics)
    • Visualization with matplotlib + seaborn
    • Mini-projects: data analysis, simple games, web scraping
  4. 04 Machine Learning Foundations (6 weeks)
    • Supervised vs unsupervised learning intuition
    • scikit-learn introduction
    • Building first ML models: regression, classification, clustering
    • Project: predict student performance from a dataset
    • Model evaluation and limitations
  5. 05 Building with AI APIs (4 weeks)
    • Calling Claude / OpenAI APIs from Python
    • Building a simple chatbot
    • Building a summarization tool
    • Connecting AI to real applications
  6. 06 Final Portfolio Project (2 weeks)
    • Each student builds a complete AI project
    • Examples: study assistant chatbot, smart flashcard app, image classifier
    • Deployment, demo presentation, portfolio documentation
    • Showcase event for parents and peers
Results

Numbers that speak.

Real results from real students at iLearn Scholars. Last 3 years\u2014board exams, JEE, NEET, MHT-CET.

Top board scores in
95%+

Top board scores in last 3 years

JEE / NEET selections
150+

JEE / NEET selections since 2020

Students above 99 %ile
12

Students above 99 %ile in JEE Mains 2025

Students taught across programs
2,000+

Students taught across programs

Top performers

  • AS
    Aarav S.
    JEE Advanced AIR 1,247
    IIT Bombay
  • PM
    Priyanka M.
    NEET 2024: 705/720
    AFMC Pune
  • RK
    Rohan K.
    Class 10 Boards: 99.2%
    School Topper
FAQ

Questions about AI for Students

Can\u2019t find your answer? WhatsApp us\u2014we usually reply within an hour during business days.

Ask on WhatsApp \u2192
What's the difference between this and a typical “kids coding” class?

Typical kids coding classes teach Scratch, basic HTML, or block-based languages. Our AI for Students program teaches actual Python, real machine learning libraries, and how to build with modern AI APIs. Our students leave with portfolio projects they can show in college applications, not toy demos.

Does my child need prior coding experience?

No. The Foundation track starts from scratch — no prior coding required. We've designed the curriculum so an absolute beginner in class 9 can graduate as a competent AI builder. Students with some Python background are placed in an accelerated track.

Will this hurt my child’s board exam preparation?

No. The program runs only on weekends (4 hours/week total) and is designed to enhance critical thinking and problem-solving — skills that improve board exam performance, not detract from it. Many of our AI students score in the top percentiles in boards and JEE/NEET as well.

What technology / equipment is needed?

A laptop (Windows, Mac, or Chromebook) with internet access. We provide all software setup support, free coding environments (Google Colab, free tier), and assist with any tooling needs. No special hardware required.

What kind of projects do students build?

Real, working AI applications. Recent student projects include: a study assistant chatbot using Claude API, a quiz-generation app from textbook PDFs, an image classifier for plant species, a sentiment analyzer for social media posts, and a flashcard app with AI-generated explanations. Every student finishes with a portfolio they can show.

Why should we pay for this when there’s free YouTube content?

Free content teaches you what AI is. Our program teaches you how to think with AI, build with AI, and apply AI to real problems — with structured curriculum, expert mentorship, hands-on project review, and a peer learning environment. The difference is the same as watching cricket vs being coached to play it.