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所在平台: Udemy |
课程主页: https://www.udemy.com/course/scientific-computing-in-c/
课程评论：没有评论
**课程名称：C++ 科学计算** **课程概览：** 本课程旨在教授如何利用 C++ 语言进行高效的科学计算。课程假设学习者已具备一定的 C++ 基础，但也会详细介绍必要的编程概念，如向量、布尔函数、数组以及面向对象编程（继承、静态成员、虚函数、多态性）的核心知识。 课程内容包括： * **基础算法：** 线性搜索、二分搜索。 * **高级排序算法：** 冒泡排序、堆排序。 * **基础编程实践：** 度分制转弧度制、二进制转十进制转换器等小程序的编写。 * **进阶概念：** 递归函数与 for 循环的对比、switch 语句、指针、函数指针、`typedef`、`enum`、`struct` 类型、动态数组（内存分配）等。 * **文件处理：** 解析多种格式文件进行后处理。 * **数值计算方法：** * 蒙特卡洛模拟（二维伊辛模型） * 辛普森积分法 * 二项分布/二项系数 * 理查森外插法进行数值微分 * 牛顿法求根 * 高斯/正态分布 * 高斯最小二乘法进行线性/指数回归 **课程目标：** 掌握 C++ 编程语言，并能熟练运用各种数值计算方法解决科学计算问题。 **适用人群：** 希望深入学习数值计算技术的学习者。
C++ is an excellent programming language which is extremely well-suited for scientific computing. I do not start from scratch, so it is good if you have some experience with C++. However, I'll try to introduce fundamental programming concepts (vector & boolean functions, arrays etc.) which are needed to understand and solve the discussed coding problems. In particular, concepts needed to understand object-oriented programming like inheritance, static members, virtual functions and polymorphism will be explained in detail. So don't panic:-).As a starter, we'll take a look at some basic algorithms such as linear & binary search. Couple tutorials down the road, we'll take a look at more advanced sorting algorithms like bubble & heapsort algorithms. Before heading towards the heart of C++, we start with coding some small programs such as degree to radian and binary to decimal number converter in order to internalize the required programming concepts. Moreover, we elaborate on recursive functions vs. for-loops with regard to advantages and disadvantages. More programming concepts involve switch functions, pointers and function pointers, typedef-constructs, enum & struct type, dynamical arrays using memory allocation and much more. Furthermore, we will learn how to parse multiple format files for post-processing.After acquiring the required knowledge, we focus more detailed on numerical methods in terms of scientific computing such as Monte-Carlo simulation of a 2D Ising magnet, integration method according to Simpson's rule, binomial distribution/coefficients, numerical differentiation using extrapolation technique by Richardson, Newton-method for finding roots, Gaussian/Normal distribution, linear/exponential regression using least square method by Gauss and so forth.So, if you want to learn numerical computation techniques in detail, you are absolutely at the right place! In this sense, I hope to see you in the course and let's start coding!
