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所在平台: Udemy |
课程主页: https://www.udemy.com/course/cpp-for-scientific-programming/
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课程名称：完整的 C++ 科学编程包 - 21 小时！ 课程概述： 《科学编程与 C++》是一门最简单、最创新、也是最全面的实践性 C++ 课程，旨在帮助学习科学与研究数据编程。尽管 Python 和 R 在科学编程或数据科学领域日益流行，但 C/C++ 在高效和有效的科学计算中仍然是更强的选择。本课程将使用最新的 C++17 进行科学编程，重点在于从初学者到高级编程在高性能计算机上的应用、面向对象软件设计、基于模板的通用编程及数值算法的高效实现。 课程内容包括： - C++ 编程基础概念的掌握； - 运用现代 C++ 编程，包括通用编程和高级技术，例如元编程、表达式模板和概念； - 使用编程工具进行代码调试、基准测试和管理，涵盖编译器、构建系统、版本控制、调试器和分析器等； - 阅读、理解和利用科学软件库，如 BLAS、LAPACK、STL、Boost 等； - 学习高性能计算中的编程，使用 OpenMP 和 MPI。 课程特点： - 包含众多实践练习，以增强 C++ 编程技能。 - 通过 Zoom 现场课程系列详细讲解 C++17 的不同方面。 - 学生可获得科学编程学校的互动版本课程免费访问权。 - 提供问答环节，可与讲师讨论课程内容或解决编程疑问。 录取要求： - 学员需具备基本的 C++ 知识。 - 本课程为自学型，提供 Linux 环境支持。 课程优势： - 从基础到高级 C++ 17 的全面理解。 - 学习开发复杂 C++ 科学应用的知识。 - 了解 C++ 库 STL、BOOST、MPI、OpenMP 的使用。 - 为申请开发岗位、博士和研究职位打下良好基础。 此课程承诺提供 30 天退款保证，注册后可终身访问所有课程内容和未来更新，并在完成课程后获得结业证书。
The 'Scientific Programming with C++' is easiest and the most innovative and complete hands-on practical C++ course on the Udemy Platform 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. 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! Main learning goals in this awesome course can be formulated as:COURSE FEATURESGet 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 interactive exercises to practice the C++. programming.Based on your earlier feedback, we are introducing a Zoom live class lecture series on this course through which we will explain different aspects of the C++17. Live classes will be delivered through the Scientific Programming School, which is an interactive and advanced e-learning platform for learning scientific coding. Students purchasing this course will receive free access to the interactive version (with Scientific code playgrounds) of this course from the Scientific Programming School (SCIENTIFIC PROGRAMMING IO). Instructions to join are given in the bonus content section.Q & APlease use the Q & A feature on Udemy to ask questions! We'd love to talk about why regular expressions don't seem to be working, discussing decisions we made about course content, and debating regular expression philosophy. There's no risk involved in taking this Course! This course comes with a 30-day money-back guarantee. Once you Enroll for this Course, you get lifetime access to this course and you will get all the future updates. you also get a Certification of Completion once you complete the course.REQUIREMENTSYou 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++
