Python中的数据结构和算法课程 Data Structures and Algorithms in Python (2023)

通过综合动画逐行可视化数据结构和算法的内部运作，构建可靠且高性能的软件需要超越特定编程语言或框架的知识。它需要深入了解数据在内存中的组织方式，以及如何操作、排序或搜索数据。谷歌、亚马逊或 Netflix 等所有大型科技公司都将技术面试重点放在这些主题上是有原因的。无论您从事移动应用程序、网站、游戏、机器学习还是任何其他涉及编码的工作，您都需要很好地掌握数据结构和算法。 许多自学的开发人员和有抱负的工程师在必须决定正确的数据结构或解决问题的正确方法时常常感到自己缺乏知识。如果您有这种感觉，那么这种材料就是您的正确选择。

本课程包含数月的计算机科学主题，可让您达到与计算机科学学位人员相同的熟练程度。是什么让我们与众不同？ 每个视频都以对当前主题的深入分析开始。在这个阶段，我们还不会编写任何代码，而是学习如何处理问题，思考解决问题的方法并建立解决方案的心理模型。 然后我们继续逐步编写算法。但我们并不止于此。我们举一个或多个例子并逐行浏览代码。我们的意思是字面上的意思。您将看到代码如何从上到下运行以及数据在执行过程中如何流动和变化。我们发现这种方法绝对是真正理解算法内部工作原理的最佳方法。我们还将分析使用 Big O 表示法编写的每个算法和方法的时间性能和空间利用率。我们将讨论每种数据结构的优点和缺点，并讨论它们在现实世界中的用法。除此之外，您还将学习诸如递归、计算机如何在幕后工作、问题解决技术、常见编程模式等等之类的知识。

本课程涵盖什么内容？计算机如何在幕后工作什么是数据结构什么是数据结构算法是问题解决技巧大O表示法——如何分析算法的时间性能和空间利用率。我们编写的每个函数/算法都会这样做。更深入地了解代码如何工作递归数据结构：数组哈希表单向链表双向链表堆栈队列二叉搜索树树遍历堆图排序算法：插入排序选择排序冒泡排序壳排序堆排序合并排序快速排序基数排序感谢您的考虑，我希望本课程对您的旅程有所帮助。快乐学习！

由 Glassbyte 团队创建
MP4 | 视频：h264，1280×720 | 音频：AAC、44.1 KHz、2 Ch
类型：电子学习 | 语言： 英语 | 持续时间：80 场讲座 (11小时 40分钟)

您将学到什么
了解计算机如何存储和处理数据
使用 Big O 表示法分析任何算法的空间和内存利用率
深入了解函数执行机制并揭开递归概念的神秘面纱
从头开始​​实现最常见的 9 种数据结构
了解最著名的 8 种排序算法的工作原理
了解树和图的搜索/遍历算法
提高解决问题的能力
了解基本数据结构（数组和哈希图）的幕后知识
了解常见的编程模式
了解您需要了解的一切技术面试

要求
任何编程语言的基本编码概念
无需具备数据结构和算法知识 用于
练习的计算机（Windows、Mac 或 Linux）

Visualize the inner workings of data structures and algorithms, line by line, through comprehensive animations

What you’ll learn
Understand how computers store and work with data
Analyze the space and memory utilization of any algorithm using the Big O Notation
Dive deep into the mechanisms of function execution and demystify the concept of Recursion
Implement from scratch the most common 9 Data Structures
Understand how the best known 8 sorting algorithms work
Learn the searching / traversing algorithms for trees and graphs
Improve your problem solving skills
Learn the behind the scenes of the basic data structures (arrays and hash maps)
Understand common programming patterns
Learn everything you need to know for the technical interview

Requirements
Basic coding concepts in any programming language
No previous data structures and algorithms knowledge needed
A computer to practice on (Windows, Mac or Linux)

Description
    Building reliable and highly performant software requires knowledge that goes beyond a certain programming language or framework. It requires a solid understanding of how data is organized in memory, how it can be manipulated, sorted or searched into. There’s a reason why all the big tech companies such as Google, Amazon or Netflix focus their technical interviews on those topics. Whether you do mobile apps, websites, games, machine learning or any other work that involves coding, you need a good grasp of Data Structures and Algorithms.    Many self taught developers and aspiring engineers often feel they lack the knowledge when having to decide on the right data structure or the right approach for solving a problem. If you ever felt that way, this material is the right choice for you. This course packs months of Computer Science subject matter to get you on the same level of proficiency as someone with a Computer Science degree.What sets us apart ?    Every video begins with an in depth analysis of the topic at hand. At this stage we won’t write any code yet, but rather learn how to approach the problem, think of ways we could solve it and build a mental model of the solution.    We then go on to code the algorithm step by step. But we don’t stop there. We take one or more examples and walk through the code line by line. And we mean that literally. You will see how the code runs from top to bottom and how data flows and changes during execution. We find this method the absolute best way to really understand the inner workings of an algorithm.    We’ll also analyze the time performance and space utilization of every algorithm and method we write using the Big O Notation. We’ll talk about the strengths and weaknesses of each data structure and discuss their real world usage. Apart from all of that, you’ll also learn things like recursion, how computers work under the hood, problem solving techniques, common programming patterns and much more.What does this course cover ?How computers work under the hoodWhat a data structure isWhat an algorithm isProblem solving techniquesBig O Notation – how to analyze the time performance and space utilization of algorithms. This is done for every single function/algorithm we write.Gain a deeper understanding of how code worksRecursionData Structures:ArraysHash TablesSingly Linked ListsDoubly Linked ListsStacksQueuesBinary Search TreesTree TraversalHeapsGraphsSorting Algorithms:Insertion SortSelection SortBubble SortShell SortHeap SortMerge SortQuick SortRadix SortThanks for considering, and I hope this course will help you in your journey. Happy learning!