Welcome to the Calculus With Python project by Mike X Cohen!
This repository contains all the code used in two companion Udemy courses on calculus:
Both courses combine traditional mathematical instruction with hands-on coding in Python. The idea is simple: you can learn a lot of math with a bit of code. By using Python (especially numpy, sympy, and matplotlib), you'll build visualizations, test ideas, and implement core concepts from calculus.
This repository is organized into two main folders:
This folder contains all Python code for the Calculus 1: Derivatives course. Topics include:
- Python introduction
- Functions
- Limits and the definition of the derivative
- Rules of differentiation (chain, product, quotient)
- Higher-order derivatives
- Symbolic and numeric differentiation using Python
Course link on self-hosted website
This folder contains all Python code for the Calculus 2: Integrals course. Topics include:
- Indefinite and definite integrals
- Fundamental theorem of calculus
- Riemann and Lebesgue integration
- Symbolic and numerical integration
- Applications to area, volume, and probability
- Multivariable integration and partial integrals
Course link on self-hosted website
These courses are for learners who want to go beyond memorizing formulas — and instead understand calculus by actively exploring it through programming. Whether you're a university student, a data scientist brushing up on math, or a lifelong learner, you'll find something here to sharpen your intuition and build practical skills.
All code is written in Python 3 and designed to be easy to follow, modify, and extend. The code is designed to be run in Python Jupyter notebooks, and I recommend running it on Google Colab.