Thread by @LearnWithBishal

Most people stop learning math after school.

Big mistake.

AI runs on math.

So does problem-solving, decision-making, and clear thinking.

Here's the roadmap I wish I had years ago:

1. Start with Algebra.

It's the foundation of everything that comes next.

Skip it, and higher math feels like random symbols.

Don't optimize for speed.

Optimize for clarity.

When each step makes sense, everything compounds from there.

📕Free resource:

The Organic Chemistry Tutor (YouTube)

Probably taught more people algebra than most schools.

2. Equations aren't math problems.

They're cause-and-effect maps.

The faster you see relationships, the faster you solve problems.

Next: Geometry.

It's not about memorizing shapes.

It's about training your brain to see patterns everywhere.

3. Learn to switch between pictures and equations.

See a diagram → write the equation.

See an equation → visualize the shape.

This is where math starts to feel intuitive.

4. Learn vectors early.

They're one of the most useful ideas in math.

Vectors connect algebra, geometry, physics, graphics, and AI.

Master them once, and you'll see them everywhere.

📚 Free resource:

3Blue1Brown > Essence of Linear Algebra (YouTube)

One of the best math series ever created.

5. Most people think trigonometry is about triangles.

It's not.

It's about rotation, waves, and patterns.

Think of sine and cosine as functions, not formulas to memorize.

Learn trig through the unit circle.

Not endless identities.

If you can visualize it, you'll never need to memorize it.

6. Precalculus is where everything clicks.

Algebra. Functions. Trig.

It connects the dots before calculus arrives.

Skip this step, and calculus feels impossible.

If precalc feels confusing, don't push forward.

Go back.

Fix the foundation.

Calculus doesn't create weaknesses.

It exposes them.

📚 Free resource:

Professor Leonard (YouTube)

Hands down one of the best free math teachers online.

7. Calculus begins with a simple idea:

Change.

Before memorizing formulas, understand what a derivative actually measures.

How fast something is changing right now.

Here's the question that powers calculus:

"What happens if I change this slightly?"

Ask it everywhere.

In math.
In business.
In AI.
That's derivative thinking.

8. Don't use calculus to solve equations.

Use it to understand behavior.

Growth.
Decay.
Optimization.
Prediction.
That's where the real value is.
Integration is accumulation.
Area under a curve is just one application.

The better question is:

"What am I adding up?"

Once you understand that, integration becomes intuitive.

9. Calculus II breaks most people.

Not because it's impossible.

Because they memorize techniques instead of understanding when to use them.

The tool matters less than knowing why it exists.

Learn limits deeply.

They're the idea that makes calculus possible.

Without limits, derivatives and integrals are just magic tricks.

10. Most people learn what to think.

Logic teaches you how to think.

It forces you to question assumptions, spot flaws, and reason clearly.

That's a superpower in the AI age.

Proofs aren't about being clever.

They're about being precise.

Follow every step until nothing feels like magic.

The goal isn't the answer.

The goal is understanding why it's true.

📚 Free resource:

Book of Proof (free online)

One of the best introductions to mathematical thinking and proofs.

11. If you're interested in AI, don't skip Linear Algebra.

It's the language behind modern machine learning.

Vectors. Matrices. Transformations.

This is where math starts feeling powerful.

Stop thinking of matrices as spreadsheets of numbers.

Think of them as machines that transform space.

That one mental shift makes Linear Algebra 10x easier to understand.

12. Eigenvalues sound complicated.

The idea isn't.

They tell you what stays stable, what grows, and what disappears over time.

That's why they show up everywhere from physics to AI.

Multivariable Calculus is where math starts looking like reality.

Because real-world problems rarely have one input.

Markets.
Weather.
Businesses.
AI models.
Everything interacts with everything else.

The foundation is done.

Now here's where all of this math actually gets used:

📌Want to become an engineer?

Focus on:

• Calculus
• Linear Algebra
• Optimization
Most engineering problems are really about building systems that work reliably.
Want to understand AI?

Start here:

• Linear Algebra
• Probability
• Optimization

These 3 topics power almost everything in modern machine learning.

📌Want to become a data scientist?

Learn:
• Statistics • Linear Algebra • Basic Calculus
The biggest mistakes come from bad assumptions, not bad tools.
📌Interested in finance?

Study:

• Probability • Calculus • Linear Systems

Because investing is really a game of risk and uncertainty.

📌Want to understand how the universe works?

Learn:
• Calculus • Linear Algebra • Differential Equations
That's the language physics is written in.

📌Interested in computer graphics or game development?

Master:

• Linear Algebra • Geometry • Trigonometry
Every 3D world starts here.

📌Building robots, drones, or autonomous systems?

Study:

• Linear Algebra • Eigenvalues • Calculus

The entire field revolves around one question:
Will the system stay stable?
Want to do research?
Focus on:

• Logic • Proofs • Modeling

Knowing why something works is more valuable than knowing that it works.

The biggest lesson:

You won't use every formula.
You will use the thinking.
That's what math is really teaching you.