Artificial Intelligence is everywhere right now — buzzing in classrooms, powering apps, and turning ideas into prototypes faster than anyone expected. And at the centre of all this movement are AI engineers: the architects who blend logic, creativity, and code to bring intelligent systems to life.
The path to becoming an AI engineer doesn’t start with fancy models or flashy tools. It begins with the strongest foundations in Computer Science, courses that teach you how to think, not just how to code. Programs in computational thinking, data science, introductory Python, AI fundamentals, and software construction train your brain to break down problems, reason clearly, debug thoughtfully, and rebuild better each time.
This mix — deep CS fundamentals, modern AI tools, and creator-mindset thinking is what shapes young builders into real AI engineers.
It’s the same pathway I followed and the same pathway we now give students through IvySchool.ai, so kids everywhere can access world-class learning early.
If you want to grow in this field, here are the steps that actually matter:
Start with the fundamentals
Everyone wants to jump straight into AI — chatbots, APIs, instant prototypes, “build this app for me” prompts. But none of it stands without a solid base in Computer Science.
The courses that shaped my thinking included:
- Harvard – Introduction to Computer Science
- MIT – Computational Thinking & Data Science
- Harvard – Web Programming with Python and JavaScript
- Harvard – Introduction to Artificial Intelligence
- Stanford – Deep Learning Specialization
- Stanford – Large Language Models
- MIT – Generative AI: Models & Applications
These courses weren’t just “classes.” They were like learning the alphabet of the digital world.
That’s why IvySchool.ai begins with real CS foundations before anything else — strong roots create strong builders.
Learn to build with AI, not just use it
AI tools evolve fast. Cursor can generate entire codebases, Claude can structure logic, Replit lets kids build apps in minutes, and Lovable turns sketches into prototypes instantly. But AI is an assistant, not the engineer. It can write code, but it can’t explain why that code fails. It can create models, but it can’t judge fairness or bias. Real CS understanding gives you judgment, and AI tools give you speed — together, they let you build real products.
Enhance your credentials
In a competitive field like AI, standing out matters. Renowned certifications from Harvard, Stanford and MIT — from IvySchool.ai — can give you a distinctive edge. These certifications validate your skills, prove your commitment to serious learning, and show future employers, mentors, or collaborators that you’re building your career with intention. Credentials don’t replace ability, but they amplify it — and in a fast-growing field, they help you rise above the noise.
Commit to lifelong learning
AI changes constantly — almost daily. New models appear, new frameworks rise, new methods reshape the world. To stay relevant, you have to stay curious. Read research papers. Watch talks. Experiment with new tools. Take courses when you outgrow old ones. The people who stay students forever become the ones who lead the field.
Kids today aren’t just “digital natives.” We’re digital creators, growing up with university-level knowledge, powerful tools, and global communities at our fingertips.
If you follow a path built on fundamentals, creativity, and relentless learning and surround yourself with the right structure, like we offer at IvySchool.ai — you won’t just enter the AI world. You’ll help shape it.
(Bob Chopra, based in US is a 9-year-old entrepreneur, who founded IvySchool.ai in 2022)
