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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-structures
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课程名称：数据结构 课程概述：高效的算法往往与一组优良的数据结构相结合，从而使算法能够高效地操作数据。本在线课程将探讨在各类计算问题中常用的数据结构。你将学习这些数据结构在不同编程语言中的实现，并通过编程作业进行实践。这将帮助你理解内置数据结构实现的内部机制及其期望效果。你还将学习这些数据结构的典型应用场景。 课程内容包括： 1. 动态数组的扩展策略 2. 在C++、Java和Python中如何实现优先队列 3. 如何实现一个平均时间复杂度为O(1)的哈希表 4. 保持二叉树平衡的优秀策略 此外，你还将了解Dropbox等服务如何迅速上传大文件并节省存储空间。 课程大纲： 1. 基础数据结构：学习数组和链表作为基础构建块，进而构建栈和队列，了解树的实现和遍历。 2. 动态数组与摊销分析：讨论在不知元素数量的情况下如何使用动态数组，以及如何应用摊销分析确定操作的平均成本。 3. 优先队列和不相交集合：学习如何实现优先队列，以高效调度任务，并了解其在动态图连接和图像处理中的应用。 4. 哈希表：学习哈希技术的强大应用，包括编程语言实现、文件系统等，掌握如何实现高效的哈希表。 5. 二叉搜索树：探索用于动态变化的有序集合的搜索结构，学习如何保持树的平衡。 6. 二叉搜索树2：继续研究二叉搜索树的非平凡应用，学习Splay树的动态适应查询功能。 通过本课程的学习，学员将掌握多种数据结构的实现及其性能分析，为后续的计算机科学学习打下坚实的基础。
Name:Basic Data Structures
Description:In this module, you will learn about the basic data structures used throughout the rest of this course. We start this module by looking in detail at the fundamental building blocks: arrays and linked lists. From there, we build up two important data structures: stacks and queues. Next, we look at trees: examples of how they’re used in Computer Science, how they’re implemented, and the various ways they can be traversed. Once you’ve completed this module, you will be able to implement any of these data structures, as well as have a solid understanding of the costs of the operations, as well as the tradeoffs involved in using each data structure.
Name:Dynamic Arrays and Amortized Analysis
Description:In this module, we discuss Dynamic Arrays: a way of using arrays when it is unknown ahead-of-time how many elements will be needed. Here, we also discuss amortized analysis: a method of determining the amortized cost of an operation over a sequence of operations. Amortized analysis is very often used to analyse performance of algorithms when the straightforward analysis produces unsatisfactory results, but amortized analysis helps to show that the algorithm is actually efficient. It is used both for Dynamic Arrays analysis and will also be used in the end of this course to analyze Splay trees.
Name:Priority Queues and Disjoint Sets
Description:We start this module by considering priority queues which are used to efficiently schedule jobs, either in the context of a computer operating system or in real life, to sort huge files, which is the most important building block for any Big Data processing algorithm, and to efficiently compute shortest paths in graphs, which is a topic we will cover in our next course. For this reason, priority queues have built-in implementations in many programming languages, including C++, Java, and Python. We will see that these implementations are based on a beautiful idea of storing a complete binary tree in an array that allows to implement all priority queue methods in just few lines of code. We will then switch to disjoint sets data structure that is used, for example, in dynamic graph connectivity and image processing. We will see again how simple and natural ideas lead to an implementation that is both easy to code and very efficient. By completing this module, you will be able to implement both these data structures efficiently from scratch.
Name:Hash Tables
Description:In this module you will learn about very powerful and widely used technique called hashing. Its applications include implementation of programming languages, file systems, pattern search, distributed key-value storage and many more. You will learn how to implement data structures to store and modify sets of objects and mappings from one type of objects to another one. You will see that naive implementations either consume huge amount of memory or are slow, and then you will learn to implement hash tables that use linear memory and work in O(1) on average! In the end, you will learn how hash functions are used in modern disrtibuted systems and how they are used to optimize storage of services like Dropbox, Google Drive and Yandex Disk!
Name:Binary Search Trees
Description:In this module we study binary search trees, which are a data structure for doing searches on dynamically changing ordered sets. You will learn about many of the difficulties in accomplishing this task and the ways in which we can overcome them. In order to do this you will need to learn the basic structure of binary search trees, how to insert and delete without destroying this structure, and how to ensure that the tree remains balanced.
Name:Binary Search Trees 2
Description:In this module we continue studying binary search trees. We study a few non-trivial applications. We then study the new kind of balanced search trees - Splay Trees. They adapt to the queries dynamically and are optimal in many ways.
A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures. A few examples of questions that we are going to cover in this class are the following: 1. What is a good strategy of resizing a dynamic array? 2. How priority queues are implemented in C++, Java, and Python? 3. How to implement a hash table so that the amortized running time of all operations is O(1) on average? 4. What are good strategies to keep a binary tree balanced? You will also learn how services like Dropbox manage to upload some large files instantly and to save a lot of storage space!
