Algorithmic Toolbox

开始时间: 04/22/2022 持续时间: Unknown

所在平台: CourseraArchive

课程类别: 计算机科学

大学或机构: CourseraNew



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The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second). Do you have technical problems? Write to us:

算法工具箱:本课程涵盖了基本算法技术和解决实际应用中经常出现的计算问题的思想:排序和搜索,分治法,贪婪算法,动态编程。我们将学到很多理论:如何对数据进行排序以及如何对数据进行搜索;如何将大问题分解并递归解决;贪婪地进行时有意义;在基因组研究中如何使用动态编程。您将练习解决计算问题,设计新算法并有效实施解决方案(以使它们在不到一秒钟的时间内运行)。 你有技术上的问题吗?写信给我们


Welcome to the first module of Data Structures and Algorithms! Here we will provide an overview of where algorithms and data structures are used (hint: everywhere) and walk you through a few sample programming challenges. The programming challenges represent an important (and often the most difficult!) part of this specialization because the only way to fully understand an algorithm is to implement it. Writing correct and efficient programs is hard; please don’t be surprised if they don’t work as you planned—our first programs did not work either! We will help you on your journey through the specialization by showing how to implement your first programming challenges. We will also introduce testing techniques that will help increase your chances of passing assignments on your first attempt. In case your program does not work as intended, we will show how to fix it, even if you don’t yet know which test your implementation is failing on.



The course covers basic algorithmic techniques and ideas for computational problems arising frequent


算法工具箱 数据结构 算法 数据结构和算法 数据结构与算法专项课程