In today’s fast-paced world of AI, Machine Learning, and Data Science, there’s a growing trend among beginners: jump straight into projects and learn the theory later. It sounds efficient. It feels productive.
"But is it the right way to learn?
Let’s talk about it.
Many posts and videos today say things like:
"“Don’t worry about the details.”
“Avoid perfectionism as a beginner — just start building!
While this advice can be motivating, it often lacks the nuance beginners truly need.
Yes, it’s true that waiting until you “know everything” before starting is a trap. But on the flip side, completely ignoring the foundations leads to a different kind of frustration.
Jumping into projects without understanding the basics is like playing chess without knowing the rules.
You might make a few random moves. You might even win a game by chance.
But soon, you’ll:
"Hit walls you can’t get past
Make wrong decisions with no way to debug or understand them
Or worse — lose confidence and stop altogether
There’s a difference between exploring a field and building in it.
If you’re just exploring — trying out tutorials, watching guided videos, seeing what excites you — skipping a few details is okay.
But if your goal is to build meaningful, scalable, or production-ready projects, then you need solid fundamentals.
Imagine trying to build a web app for 1,000 users without knowing software engineering principles.
You might get something working.
But chances are, you’ll soon run into:
- Scalability issues
- Unmaintainable code
- Technical debt
- Systems that fall apart the moment you try to extend or improve them
The same holds true for AI & ML.
If you don’t understand:
- The math behind the models
- The assumptions each algorithm makes
- Evaluation metrics
- How training, validation, and testing work…
…then you’re not really “building” — you’re copy-pasting and hoping it works.
Here’s what I’ve learned:
"You don’t need to master every detail before starting.
But you do need to understand what you’re doing at a foundational level.
Guided projects are fine — but take time afterward to dig deeper into what made the project work.
Strong fundamentals are not about perfectionism.
They’re about clarity, confidence, and creativity.
They don’t slow you down — they save you time in the long run.
Because when things break (and they will), it’s your foundations that help you rebuild stronger.