Course Overview

Learn Computing Mathematics with Python by doing!

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.

The main objective of this course is to provide a comprehensive overview of symbolic Mathematics and Computing with Python and its applications in Engineering, Science, and Mathematics.

This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, and some you will have as homework exercises.

In summary, this course has been designed for all skill levels and even if you have no programming or computing background you will be successful in this course!

Who is this course for?

• This course is for you if you want to learn how to program with Python
• This course is for you if you want to enhance your computing skills
• This course is for you if you want to write programs to solve complex problems in Mathematics, Science, and Engineering
• This course is for you if you want to learn AI, ML, DL and their applications
• This course is for you if you want to be Data Scientist/ Analytic
• This course is for you if you want to use Python for Numerical Methods, Optimization Techniques, Computational Physics, Computing Quantum Mechanics, Mathematical Modelling, etc.

What are the requirements or prerequisites for taking your course?

No programming experience is needed. You will learn everything you need to know

Course outcomes?

after completing this course successfully, aspirants will be able to

• install Python, Anaconda, and required packages
• import libraries for computing the results
• perform algebraic manipulations on symbolic expressions
• perform basic calculus tasks (limits, differentiation, and integration) with symbolic expressions
• solve polynomial and transcendental equations
• solve some differential equations

Course Content

Unit-1: Basic Python: 1.1 getting started with Python 1.2 Python as a calculator 1.3 Managing Packages 1.4 Introduction to Jupyter NoteBook 1.5 Logical Expressions and Operators

Unit-2: Variables and Basic Data Structures: 2.1 Variables and Assignment 2.2 Data Structure-String 2.3 Data Structure-List 2.4 Data Structure-Tuple 2.5 Data Structure-Set 2.6 Data Structure-Dictionary 2.7 Introducing Numpy Arrays 2.8 Summary and Problems

Unit-3: Functions: 3.1 Function Basics 3.2 Local and Global Variable 3.3 Nested Functions 3.4 Lambda Functions 3.5 Functions as Arguments to functions

Unit-4: Branching Statement: 4.1 If-else Statement 4.2 Ternary Operators 4.3 Summary and Problems

Unit-5: Iterations: 5.1 For Loop 5.2 While Loop 5.3 Comprehensions 5.4 Summary and Statement

Unit-6: Representations of Number: 6.1 Base-N and Binary 6.2 Floating Point Number 6.3 Round-Off Errors 6.4 Summary and Problems

Unit-7: Symbolic Mathematics: 7.1 Introduction 7.2 Gotchas 7.3 SymPy Features (Basic Operations, Printing, Simplification, Calculus, Matrices)

Unit-8: Linear Algebra and System of Linear Equations: 8.1 Basics of Linear Algebra 8.2 Linear Transformations 8.3 System of Linear Equations 8.4 Solutions to System of Linear Equations 8.5 Solving System of Linear equations Python 8.6 Matrix Inversion

Unit-9: Eigen Values and Eigen Vector: 9.1 Eigen Values and Eigen Vectors Problem Statement 9.2 The Power Method 9.3 The QR Methods 9.4 Eigen values and Eigen Vectors in Python

Unit-10: Least Squares Regression: 10.1 Least squares regression problem statements 10.2 Least squares regression derivation (Linear Algebra) 10.3 Least squares regression derivation (Multivariate Calculus) 10.4 Least Squares Regression in Python 10.5 Least squares regression for non-Linear functions

Unit-11: Interpolation: 11.1 Interpolation Problem Statement 11.2 Linear Cubic Interpolation 11.3 Cubic Spline Interpolation 11.4 Lagranges Polynomial Interpolation 11.5 Newton’s Polynomials Interpolation

Unit-12: Taylor Series: 12.1 Expression functions using a Taylor Series 12.2 Approximations Using Taylor Series 12.3 Discussion About Errors

Unit-13: Ordinary Differential Equations (ODE) Initial Value Problems: 13.1 ODE Initial Value Problem Statement 13.2 Reduction of order 13.3 The Euler Method 13.4 Numerical Error and Instability 13.5 Predictor-corrector and Runge-Kutta Methos 13.6 Python ODE Solvers

Unit-14: Boundary-Value Problems for Ordinary Differential Equations: 14.1 ODE Boundary value Problems Statement 14.2 The Shooting Method 14.3 The Finite Difference Method

Unit-15: Introduction to Optimization: 15.1 Introduction 15.2 Minimization along a line 15.3 Powell’s Method 15.4 Downhill Simplex Method

Free Registration

There is no registration fee. After registration, this course will be available for 365 days after completing of the course. To register for this course download Junior STEM Foundation App from the play store and register there. The whole course will be available there. To get the certificate, the candidate has to complete the course successfully. After completion, the candidate can request to get the certificate, which will be provided by MTTF with ISO certification. The fee for the certificate is 500 INR/10 USD. The course is available on MathTechEdu and Junior STEM Foundation. Only Indian candidates can download Junion STEM Foundation APP. To register the course Click here.

To download Junior STEM Foundation App: Click here

This course is available in-store, after login the app, user can easily find in store. Also note that one candidate can register at one plateform only.

Course Coordinator: Dr. Mehar Chand

He is a Professor (Assistant) in the Department of Mathematics, Faculty of Computational and Mathematical Science, Baba Farid College (Affiliated to Punjabi University, Patiala) in the Department of Mathematics, where he teaches courses and works on supporting math students and the broader math community in various ways! He is appointed as a member of the Board of Post Graduate Studies in Mathematics, (Punjabi University, Patiala).

Research Interest: His research interest is involved in fractional calculus and its applications, Mathematical Modeling, Numerical Methods, Computational Mathematics, Special functions, Hypergeometric functions, Mathematical Physics, ANN, ML, and DL.

Publications: He has published more than 70 research papers in national and international journals (including SCI, SCIE, and SCOPUS-indexed journals). He also has published 5 Book Chapters in a research book (Published by Springer)

Invited talks: He has delivered more than 40 invited talks/Keynotes in national and international workshops and conferences

Expert talks: He has delivered 39 expert talks in national and international FDP/ Workshop / Seminar.

Activities: He has organized more than 50 national and international Training Workshops/Workshops/ FDP/webinars/Seminars. Two internships (sponsored by DST), and one CSIR workshop. Membership of Academic Bodies: 05 Supervision: Under his supervision, 4 students were awarded Ph.D.