Listed below are the developed course modules:
| Name | Developer |
Github link/ Video(s) |
| Numerical Differentiation | Dr. Zheng (Leslie) Chen, Math | Github |
| Building a MATLAB App Designer application that approximates derivatives of arbitrary functions. | ||
| Numerical Integration | Dr. Zheng (Leslie) Chen, Math | |
| Building a graphical user interface (GUI) in MATLAB to approximate integrations with integrand and numerical methods as user inputs. | ||
| ODE Solver | Dr. Zheng (Leslie) Chen, Math | Github |
| Building a graphical user interface (GUI) in MATLAB to solve initial value problems of ordinary differential equations (ODEs). | ||
| Python and Git Setup | Dr. Scott Field, Math | |
| Helping students setup their computers to use Python and Git, while providing some exposure to the command-line. It’s intended for students who have never used Python or Git, but could be helpful for students of all levels. The instructions are applicable for Linux, MacOS, and Windows operating systems. | ||
| Algorithmic Thinking | Dr. Bob Fisher, Physics | Github |
| A gentle introduction to algorithmic thinking, with an application to projectile motion | ||
| Tangent Approximation | Dr. Adam Hausknecht, Math | |
| This module will introduce students to methods for approximating the tangent to the graph of a function. For this module, you will complete a Python 3 – Matplotlib application that uses secants to approximate the tangent line to the graph of a function at a point. The entire program is about 470 lines of Python 3 code but you will only need to write about 20 lines of code. The app was written using the Anaconda Python Distribution using the Spyder IDE. The app runs under Mac OS Catalina, Mac OS Big Sur, Ubuntu 20.04, and Windows 10. | ||
| Atomic/Molecular Orbital Visualization | Dr. Maricris Mayes, Chemistry | Github |
| Plotting the wavefunction for the particle in a box and their corresponding probability densities. | ||