Welcome to the official code repository for the Calculus 2: Integrals course on my self-hosted site, created by Mike X Cohen.
This repository contains all the Python code used in the course, including:
- Code demonstrations that accompany each video
- Exercise solutions (fully explained in the videos)
- Additional resources and visuals to support your learning
The goal of this course (and this repo) is to help you learn integral calculus by doing calculus — and Python is your tool for exploring, visualizing, and deeply understanding derivative concepts.
The course covers the following major topics:
- Intuition for integration
- Geometric approximations
- Integrating functions
- Improper integrals
- Integration techniques
- Applications in geometry
- Applications in statistics
- Multivariable integration
To run the code, you'll need Python (3.7 or newer) and the following Python libraries:
- numpy
- matplotlib
- sympy
- scipy
However, I recommend following along with the course using Google Colab. It has all the Python libraries already installed, so you can just immediately start coding. If you want to run the code locally on your computer, I recommend installing Jupyter notebooks via Anaconda.
Recommendation: Download the code in this repo (or clone it), upload it to your Google Drive, then open the files in Colab while following along with the videos.
- Each folder in this repo corresponds to a section of the course
- The filenames within each folder are
<course>_<section>_<video>.ipynb - Filenames with
CCin the video titles correspond to "Code Challenge" videos.
- Follow along with the course on Udemy
- Use the code to experiment with concepts: try modifying equations, creating new plots, or implementing your own problems
- Use the exercise solutions (in the "code challenge" videos) to check your understanding or troubleshoot your own solutions