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Scientific Programming Team for Scientific Programming School

Posted on • Updated on • Originally published at school.scientificprogramming.io

How to Learn Scientific Programming with C++?

Do you wish to learn programming? There are a plenty of courses online, but hardly you will find one that takes you to the next level of programming: Introducing the “Scientific Programming with C++”.

The “Scientific Programming with C++” is easiest and the most innovative hands-on practical C++ course for learning scientific and research data programming! It is also a finest example of Devops with Docker, Judge-API and TTYD technologies. We used these to build this course and we took 6-8 months of Devops times to build and cater the IDE environments for you.

While languages like Python and R are increasingly popular for Scientific Programming or Data sciences, C/ C++ can be a stronger choice for efficient and effective data and scientific computing. In this course, we hands-on the latest C++17 for Scientific Programming, software libraries, like MKL(Intel® Math Kernel Library), BLAS (Basic Linear Algebra Subroutines), LAPACK (Linear Algebra Package), STL (Standard template library), Boost (portable C++ library), MPI, OpenMP, CUDA and so on!

There are numerous hands-on to practice the C++ programming throughout the course. Happy coding!

Requirements

You will need a grasp of basic C++. It is a self-learning course with all Linux and IDE environments are provided.

Outcome

Understand programming C++ basics to the advanced C++ 17
Knowledge on developing complex C++ scientific applications
Learn about C++ libraries STL, BOOST, MPI, OpenMP
Be in a position to apply for Developer jobs, PhD and research positions requiring good C++

Get it now!

Scientific Programming with C++

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