Symbolic Mathematics with Python: An Introduction

About this tutorial series
The main objective of this tutorial series is to provide a comprehensive overview of symbolic Mathematics with Python and its applications in Engineering, Sciences and Mathematics. The workshop will provide an excellent opportunity for participants to meet and exchange ideas of common interests and to discuss new challenges faced by our academic community working in this area from different institutions and universities around the world. The training will motivate and educate the participants to develop computing skills among themselves. The procedure we intend to use in achieving this is by having resource persons who are knowledgeable in this field to deliver their talk and guide the participants with on hands examples and applications. Our desire is to leave an impact on the students and researchers to help them in the field of computing symbolic Mathematics with applications.

Why is Python?
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built-in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python’s simple, easy-to-learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed.

Contents for training
Introduction: Introduction to Python, Python Packages, Anaconda, Python Editors (Python IDLE, Visual Studio Code, Spyder, Visual Studio, PyCharm, Wing Python IDE, Jupyter Notebook)

Installing Python: Python Windows 10 Store App, Installing Anaconda, Installing Visual Studio Code

Basic Python Programming: Basic Python Program, Variables, Built-in Functions, Python Standard Library, Using Python Libraries, Packages and Modules, matplotlib – 2D and 3D plotting in Python

Basic Operations: Substitution, Converting Strings to SymPy Expressions, evalf, lambdify

Simplifications: Polynomial/Rational Function Simplification, Trigonometric Simplification, Powers, Exponentials and logarithms, Special Functions

Matrices Basic: Operations, Basic Methods, Matrix Constructors, Advanced Methods, Possible Issues

Calculus: derivative, integration, limit, series expansion, ode and pde

Solvers: A Note about Equations, Solving Equations Algebraically, Solving Differential Equations

Basics of Optimization Techniques

Mentor
Mehar Chand, Ph.D.
Department of Mathematics
Faculty of Computational and Mathematical Science
Baba Farid College, Bathinda, INDIA