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Numerical Python (NumPy)

Unlock high-performance vectorized math. NumPy is the engine that powers Pandas, Scikit-Learn, and all matrix operations.

4h 05min 11 lessons 12 interactive pages Intermediate

Welcome to NumPy 🔢

NumPy arrays are 10-100x faster than Python lists for numerical computing. NumPy is the foundation of the entire data science ecosystem.

Why NumPy?

  • Vectorized operations - Apply math to entire arrays instantly
  • Memory efficient - Store millions of numbers compactly
  • Broadcasting - Operations across different shapes
  • Linear algebra - Matrix multiplication, eigenvalues, solving systems
  • Random numbers - Simulations and statistical testing

Real-World Speed

Doubliing 1,000,000 numbers:

  • Python list with loop: ~100ms
  • NumPy array (vectorized): ~1ms

That's 100x faster!

Prerequisites

✅ Module 1 (Python Basics)

Let's unlock numerical superpower! ⚡

Curriculum