Date Approved
12-12-2024
Graduate Degree Type
Project
Degree Name
Applied Computer Science (M.S.)
Degree Program
School of Computing and Information Systems
First Advisor
Christian Trefftz
Academic Year
2024/2025
Abstract
This project introduces an interactive Google Colab notebook designed to familiarize users with the core functionalities of the SymPy Python library, a powerful tool for symbolic computation. SymPy offers an extensive range of capabilities essential for mathematical modeling, algebraic operations, calculus, and matrix manipulations. The notebook serves as an educational platform, allowing users to experiment with small examples and explore practical applications of symbolic computation in real time. Organized into sections, the notebook focuses on key SymPy features such as simplification, equation solving, differentiation, integration, and matrix operations. Each section includes clear explanations, practical demonstrations, and interactive exercises, helping users build confidence in applying symbolic mathematics. The interactive design encourages active participation, enabling users to modify inputs and observe immediate results, fostering a deeper understanding of underlying concepts. By engaging with this resource, users develop computational skills and problem-solving abilities while gaining insights into the real-world applications of symbolic computation. Accessible and user-friendly, the notebook caters to students, educators, and professionals, providing a solid foundation for further exploration. This project bridges the gap between theoretical mathematics and practical implementation, promoting the use of symbolic computation in diverse scientific and engineering domains, making it a valuable learning tool.
ScholarWorks Citation
Basani, Mary Deepika, "Creating a COLAB notebook based on the tutorial of the SIMPY Python library" (2024). Culminating Experience Projects. 537.
https://scholarworks.gvsu.edu/gradprojects/537
