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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: 12 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. 

More Information

 

  •  You will have gained a solid foundation in scientific computing with Python
  • Implement academic projects in Python for your M.S. / Ph.D. thesis and also for any industrial projects.
  • Write your own solver
  • To be competent in the highly demanding field of scientific computing across various disciplines in academia and industry.
  • Science and Engineering students pursuing B.Sc., B.E./B.Tech, M.Sc., MS/M.Tech, Ph.D. for their academic projects and to enhance their skills.
  • CFD Fluent users who is planning to learn PyFluent
  • Any computing enthusiasts.
  • Professors/Lecturers/Teaching Assistants who want to teach or guide their students in scientific computing projects.
  • Researchers, Scientists, or Engineers who want to shift from FORTRAN or  MATLAB to  Python
  • Professionals already working in the industry but want to improve their Python fundamentals
  • Do I get a certificate?
    Yes, based on your attendance and completion of tutorials, you will be given the certificate. 
  • Will I get placed?
    The best students will be given internship opportunities and we will forward your resumes to companies that contact us for good students. Please note that we don’t give any false promises that you will be placed.  Surely we will help the best students. 
  • Do I need a powerful workstation/computer to learn this course?
    No, a normal laptop with 4 or 8GB RAM and a decent processor (i3) is good enough for this course.
  • What if I don’t understand some portion or need to clarify some doubts?
    We will support you through emails and zoom meetings/discussion sessions to clear all doubts and questions
  • Should I know the programming or any other CFD software to learn this course? 
    Programming knowledge is not a prerequisite
  • Is there any prerequisite? 
    The course is aimed at programmers of all levels of expertise who wish to write scientific computing applications in Python. Basic familiarity with computer hardware and software, where files can be kept and edited is expected. Basic knowledge of mathematics, such as operations between vectors and matrices, and the Newton-Raphson method for finding the roots of non-linear equations would be an advantage.
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Course Includes

  • 30 Lessons
  • 27 Quizzes

Ratings and Reviews

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What's your experience? We'd love to know!
Chaitanya
Posted 4 days ago
Scientific Computing with Python course review!!

If you want to learn Python programming from scratch, then this is the course!! The course provided me a comprehensive introduction to Python programming, starting from the basics and progressing towards more advanced concepts. The hands-on approach, combined with exposure to relevant libraries, indicates a focus on practical application, which is valuable for building proficiency in Python.

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Vladislav Živanović
Posted 5 days ago
Well structured, concise, inclusive, motivating

This was my first contact with Python. I loved the examples in the lectures and assignments on end of each task. The assignments are in form of homework, one needs to go through the lecture and example given in the lecture, include some creativity to solve the task. I managed to make my own blocks of code during this course which I can implement as modules in future. I recommend it!

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ajmeerasuresh08
Posted 3 weeks ago
Scientific Computing with Python

The course was well-organized, with clear explanations for each topic that were easy to follow and comprehend. It provides an ideal learning environment for beginners starting with Python.

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Raghu Karthik
Posted 2 months ago
Made it so easy to learn

Like all the other programming courses I took at FlowThermolab this one too is very good especially if we want to do scientific computing. The essential caveats that are needed for computing are layed out all along the course which comes from the experience of the instructor.

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Rahul Sunil
Posted 2 months ago
great course for engineering beginers

Overall course is good. Support team approach can be improved.

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Roshan Pradeep
Posted 4 months ago
Very good course for beginners

This course helped me to advance from a beginner level python programmer to an intermediate python programmer.

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Praveen Kumar
Posted 5 months ago
Excellent course on python with relevant contents

Great learning experience!! Course starts from basic syntax to the advance python concepts like functions, OOPs, etc. Instructor also covered important relevant libraries like numpy, scipy and matplotlib.

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CHRISTOPHER S
Posted 6 months ago
Scientific computing with Python

The course had excellent structure, and the explanations for each topic were lucid and easy to understand. It's the perfect learning environment for starting with Python from the very beginning.

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María Manuela Rosales
Posted 6 months ago
Great way to get a foundation in Python

Well distributed content, knowledge is reforced by solving quizzes and small coding challanges. I'd recommend this course.

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