Scientific Computing with Python

Course Description:

Welcome to the self-paced “Scientific Computing with Python” training course! This comprehensive program is designed for science and engineering students, professors, research scholars, and working professionals who want to enhance their scientific computing skills using Python. This is the first part of the scientific computing course which is focused more on the basics so that anyone new to programming can easily understand. A more advanced version will be the next step.

In this course, we will cover all the major topics in Python from a scientific computing perspective. We will start with an introduction to Python, exploring its applications in scientific computing and learning how to use Python as an advanced calculator in an interactive mode. You will gain hands-on experience working with strings, creating and saving Python programs, and understanding the basics of variables.

Data structures play a crucial role in scientific computing, and in this course, we will cover lists, tuples, and dictionaries. You will learn how to effectively use these data structures for storing and manipulating data. We will also explore control flow statements, including for loops, if statements, while loops, as well as break and continue statements.
The course will delve into functions, both built-in and user-defined. You will understand the concept of pass-by-value vs. pass-by-reference and learn how to work with positional and keyword arguments. We will also cover more advanced topics such as classes and objects, giving you an introduction to object-oriented programming in Python. You will learn about class attributes, methods, inheritance, and how to use objects as attributes.

To facilitate efficient coding and reusability, we will dive into writing and importing modules. This will enable you to create your own Python modules and leverage existing ones to enhance your scientific computing capabilities.
In the realm of scientific computing, the course will introduce you to essential scientific packages. We will cover Numpy, a fundamental package for scientific computing, which provides powerful tools for working with arrays and numerical operations. Scipy, another important package, will be explored for scientific and mathematical computations. Additionally, we will dive into Matplotlib, a versatile library for data visualization, empowering you to create visually appealing plots and charts to communicate your findings effectively.

By the end of this course, you will have gained a solid foundation in scientific computing with Python. You will be equipped with the skills to perform complex calculations, handle and analyse data, visualize results, and even delve into more advanced topics such as scientific packages and object-oriented programming.
This self-paced course allows you to learn at your own convenience, giving you the flexibility to study whenever and wherever you want. With practical exercises, coding examples, and real-world projects, you will be able to apply your knowledge to solve scientific problems.
Embark on this exciting journey of mastering Python for scientific computing and unlock new possibilities in your academic or professional pursuits. Enrol now and gain the skills to excel in the field of scientific computing with Python.

Key information:

• Course Instructor:   Mr. Nishant Soni. He has a master’s degree in engineering [M.S. (Engg.)] focused on high-performance computing (HPC) from the Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore. He has worked as an Applications Engineer (CFD and Heat Transfer) at COMSOL Multiphysics, Bangalore in India. Prior to joining COMSOL, he worked in the field of software development, specializing in HPC simulation solutions. He has also worked on several research projects involving high-speed unsteady aerodynamics and reduced-order modeling.
• Course content:  3 Modules- 28 Lessons (~20 hours) along with quizzes and challenges/assignments 
• Doubt clearance: Email support. 
• Discussion forum: A discussion forum to discuss any topics with fellow students and the instructor
• Total access period: 6 Months from the day of enrolling 
• Computer requirement: Minimum 4 GB RAM and i3 processor 
• Access to the course: Once you make the payment, your login ID and password will be sent automatically via email.