Simulation, Algorithm Analysis, and Pointers

所在平台: CourseraArchive

课程类别: 其他类别

大学或机构: CourseraNew

课程主页: https://www.coursera.org/archive/simulation-algorithm-analysis-pointers

课程评论:没有评论

第一个写评论        关注课程

课程大纲

File IO and Automation
Simulation and Parallelization
Algorithm Analysis
Pointers

课程评论(0条)

课程详情

This course is the fourth and final course in the specialization exploring both computational thinking and beginning C programming. Rather than trying to define computational thinking, we’ll just say it’s a problem-solving process that includes lots of different components. Most people have a better understanding of what beginning C programming means! This course assumes you have the prerequisite knowledge from the previous three courses in the specialization. You should make sure you have that knowledge, either by taking those previous courses or from personal experience, before tackling this course. The required prerequisite knowledge is listed below. Prerequisite computational thinking knowledge: Algorithms and procedures; data collection, analysis, and representation; abstraction; and problem decomposition Prerequisite C knowledge: Data types, variables, constants; STEM computations; selection; iteration (looping); arrays; strings; and functions Throughout this course the computational thinking topics you'll explore are: automation, simulation, parallelization, and algorithm analysis.For the programming topics, you'll continue building on your C knowledge by implementing file input and output in your programs and by exploring pointers in more depth. Module 1: Learn how to read, write, and append to files. Explore automation Module 2: Discover the benefits of simulation and parallelization Module 3: Learn how to perform algorithm analysis to quantify algorithm complexity Module 4: Explore how to use pointers in more depth

仿真,算法分析和指针:本课程是专业化课程中的第四门课程,也是最后一门课程,探讨计算思想和C语言入门。我们只是说这是一个解决问题的过程,其中包含许多不同的组件,而不是试图定义计算思想。大多数人对开始C编程的含义有了更好的了解! 本课程假定您具有前三门专业课程的先决知识。在学习本课程之前,您应该通过上一门以前的课程或从个人经验中确保自己具有该知识。所需的必备知识在下面列出。 必备的计算思维知识:算法和过程;数据收集,分析和表示;抽象和问题分解 必备的C知识:数据类型,变量,常量; STEM计算;选择迭代(循环);数组;弦和功能 在本课程中,您将探讨的计算思想主题是:自动化,仿真,并行化和算法分析。对于编程主题,您将通过在程序中实现文件输入和输出以及探索指针来继续建立C知识。更深入。 模块1:了解如何读取,写入和附加到文件。探索自动化 模块2:了解模拟和并行化的好处 模块3:了解如何执行算法分析以量化算法复杂性 单元4:探索如何更深入地使用指针

课程标签

0人关注该课程

主题相关的课程