SciPy

Curriculum

8 chapters, each with a tutorial, a live example, a quiz, an exercise, a challenge, and class practice.

1. 1

   Introduction to SciPy

   What SciPy adds on top of NumPy.

   preview
2. 2

   Statistics Module

   Distributions and hypothesis tests.

3. 3

   Optimization Basics

   Minimizing a function with scipy.optimize.

4. 4

   Linear Algebra

   Matrix operations with scipy.linalg.

5. 5

   Interpolation

   Estimating values between known data points.

6. 6

   Signal Processing Basics

   Filtering and analyzing signals.

7. 7

   Sparse Matrices

   Efficiently storing mostly-zero matrices.

8. 8

   Integration

   Numerical integration with scipy.integrate.