😅 What I Actually Did in My First Weeks Learning Python & Machine Learning

You know the one: “A few tutorials, some practice… boom, AI engineer.”

Yeah… no.

Here’s what really happened in my first weeks learning Python and ML — no hype, just reality.

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🤯 What I Thought Learning Python & ML Would Be Like

I honestly believed:

• I’d jump straight into machine learning models
• Python would feel “natural” after a few days
• Tutorials would magically click
• Progress would be fast and obvious

Instead, I mostly stared at my screen asking:

“Why is this not working?”

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🧩 What I Actually Worked On

Spoiler: not machine learning.

My first weeks were all about Python basics (and struggling with them).

I spent most of my time on:

• 🧠 Variables, input, output
• 🔀 if / elif / else (my new enemies)
• ➕ Simple programs like calculators and BMI checkers
• 🐛 Breaking my code… then breaking it again
• 📖 Reading error messages I used to ignore

Not glamorous. Very necessary.

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😲 The Biggest Surprise

Python didn’t surprise me with syntax.

It surprised me with how much thinking it demands.

Python forces you to:

• Think step by step
• Be painfully clear with logic
• Admit when your thinking is wrong

I learned this pretty fast:

Coding isn’t about typing code — it’s about solving problems without lying to yourself.

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😵 What Was Harder Than Expected

Logic.
Basic logic.

Things like:

• ❌ Why my if condition never runs
• ❌ Why my answer is always wrong
• ❌ Why my program works once and then refuses forever

Painful lesson:

Python will happily run your code even if your logic makes zero sense.

Debugging quickly became part of my daily routine.

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🤖 How This Changed How I See Machine Learning

This phase gave me a reality check.

I now understand that:

• Weak Python basics = suffering later in ML
• Machine learning is just logic… but louder
• Skipping fundamentals is a terrible idea

So instead of rushing into ML, I slowed down — even though it felt uncomfortable.

Turns out, slowing down is progress too.

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🎯 What I’m Focusing on Next

Right now, I’m keeping it simple:

• ✅ Stronger Python fundamentals
• ✅ Small but complete programs
• ✅ Logic first, complexity later

Machine learning is still the goal.
I’m just choosing the less painful path.

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🧠 One Small Lesson I’m Taking Forward

If I had to summarize my first weeks learning Python and Machine Learning in one sentence, it would be this:

Don’t rush toward “advanced” topics when the basics are still teaching you how to think.

Learning Python slowed me down in a good way.
It forced me to stop guessing and start reasoning.

I didn’t build anything impressive yet — but I built patience, debugging skills, and a better way to approach problems.

That feels like a solid foundation.

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💬 Let’s Compare Notes

If you’re learning Python or ML right now:

What part confused you the most at the beginning?

Or what do you wish you had slowed down on?

I’d love to learn from your experience.

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👋 If you’re learning Python too, what confused you the most at the beginning?

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