C++ for Scientific Programming: OOP, Parallel & Distributed

Free Download Udemy C++ for Scientific Programming: OOP, Parallel & Distributed. With the help of this course you can From the Basics of the C++17 Object Oriented to the Advanced Libraries STL, BOOST, CUDA, OpenMP and MPI! R&D Masterclass.

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C++ is the best choice for efficient and effective programming in Research Data mining & Scientific Computing. In this course, we will hands-on the latest C++17 for Scientific Programming. Learn from the basics of C++ to the advanced and useful libraries like STL, BOOST, OpenMP and MPI!

The ‘Scientific Programming with C++’ is easiest and the most innovative hands-on practical C++ course for learning scientific and research data programming! 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.  The focus of this course lies on learning beginner to advanced programming on high-performance computers, object-oriented software design, generic or template-based programming, and the efficient implementation of numerical algorithms. Main learning goals in this awesome course can be formulated as:

COURSE FEATURES

• Get a basic concepts on the programming with C++.

• Learn how to program with modern C++, using generic programming and advanced techniques, like meta programming, expression templates, and concepts.

• Learn how to use programming tools and you can apply these tools to debug, benchmark, and manage your code. The list of tools include compilers, build systems, version control, debuggers, and profilers.

• Learn to read, understand, and utilize (scientific) software libraries, like BLAS (Basic Linear Algebra Subroutines), LAPACK (Linear Algebra Package), STL (Standard template library), Boost (portable C++ library).

• Learn how to code in HPC, using OpenMP and MPI.

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

The focus of this course lies on aspects of software development like programming on high-performance computers, object-oriented software design, generic (template-based) programming, and the efficient implementation of numerical algorithms. Additionally experience in analysis, application and extension of software and software libraries is developed.  Three main learning goals can be formulated:  You know how to program with modern C++, using generic programming and advanced techniques, like meta programming, expression templates, and concepts. You know how to use programming tools and you can apply these tools to debug, benchmark, and manage your code. The list of tools include compilers, build systems, version control, debuggers, and profilers.  You can read, understand, and utilize (scientific) software libraries, like BLAS (Basic Linear Algebra Subroutines), LAPACK (Linear Algebra Package), STL (Standard template library), Dune (framework for the discretization of partial differential equations), MTL4 (Matrix Template Library), Boost (portable C++ library).

There will be exercises to practice the C++ programming. Programming projects  are assigned.

REQUIREMENTS

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

WHY YOU SHOULD GET THIS COURSE?

•         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++