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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-structures-and-algorithms-in-depth-using-c-sharp/
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Coursera 上的《数据结构与算法：深入 DSA C# 实战》课程概览 这门课程旨在帮助学习者深入理解数据结构的基础知识以及如何在 C# 中实现算法。课程内容涵盖了从基础到高级的广泛主题，并配有理论讲解视频和 C# 实现演示： **核心数据结构与算法基础：** * 数据结构与算法基础概念 * 算法分析（Big O、时间与空间复杂度） * 递归及其递归算法分析 **基础算法：** * 查找算法 * 排序算法 **重要数据结构：** * 链表 (Linked List) * 栈 (Stacks) * 队列 (Queues) * 二叉树 (Binary Trees) * 二叉搜索树 (Binary Search Trees) * 平衡二叉搜索树 (Balanced Binary Search Trees) * 优先队列与堆 (Priority Queues and Heaps) * 哈希表 (Hashing) * 图 (Graphs) * 图遍历算法 (Graph Traversal Algorithms) **高级算法主题：** * **集合与不相交集合** * **分治法 (Divide and Conquer)：** * 基础介绍 * 二分查找 * 寻找最大值与最小值 * 归并排序 * 快速排序 * 选择算法 * Strassen 矩阵乘法 * 最近点对问题 * 凸包问题 * **贪心法 (Greedy Method)：** * 基础介绍 * 背包问题 * 带截止时间的作业排序 * 最小生成树（Prim 和 Kruskal 算法） * 树上的最优存储 * 最优合并模式 * 单源最短路径（Dijkstra 算法） * **动态规划 (Dynamic Programming)：** * 基础介绍 * 多阶段图 * 所有点对最短路径 * 单源最短路径 * 最优二叉搜索树 * 0/1 背包问题 * 可靠性设计 * 旅行商问题 * **回溯法 (Backtracking)：** * 基础介绍 * N 皇后问题 * 子集和问题 * 图的着色问题 * 哈密顿回路问题 * 0/1 背包问题 * **分支限界法 (Branch & Bound)：** * 基础介绍 * N 皇后问题 * 作业排序问题 * 0/1 背包问题 每部分都包含详细的视频教程，帮助学习者从理论到实践全面掌握数据结构与算法。
This course will help you in better understanding of the basics of Data Structures and how algorithms are implemented in C#. This course consists of Videos which covers the theory concepts + implementation in C#. There's tons of concepts and content in this course:Basics of data structures & AlgorithmsAnalysis of Algorithms (Big O, Time and Space complexity) Recursion & Analysis of Recursive AlgorithmsSearching AlgorithmsSorting AlgorithmsLinked ListStacksQueuesBinary TreesBinary Search TreesBalanced Binary Search TreesPriority Queues and HeapsHashingGraphsGraph Traversal AlgorithmsFollowed by Advanced Topics of Algorithms:Sets and Disjoint SetsDivide and Conquer Approach - IntroductionDivide and Conquer - Binary SearchDivide and Conquer - Finding Maximum and MininumDivide and Conquer - Merge SortDivide and Conquer - Quick SortDivide and Conquer - Selection AlgorithmDivide and Conquer - Strassens Matrix MultiplicationDivide and Conquer - Closest PairDivide and Conquer - Convex HullGreedy Method - IntroductionGreedy Method - Knapsack ProblemGreedy Method - Job Sequencing with DeadlinesGreedy Method - Mininum Cost Spanning Tree (Prim's & Kruskal's Algorithms)Greedy Method - Optimal Storage on TreesGreedy Method - Optimal Merge PatternGreedy Method - Single Source Shortest Path (Dijkstra's Algorithm)Dynamic Programming - IntroductionDynamic Programming - Multistage GraphsDynamic Programming - All Pairs Shortest PathDynamic Programming - Single Source Shortest PathDynamic Programming - Optimal Binary Search TreesDynamic Programming - 0/1 Knapsack ProblemDynamic Programming - Reliability DesignDynamic Programming - Travelling Salespersons ProblemBacktracking - IntroductionBacktracking - n-Queesn ProblemBacktracking - Sum of Subsets ProblemBacktracking - Graph Coloring ProblemBacktracking - Hamiltonian Cycles ProblemBacktracking - 0/1 Knapsack ProblemBranch & Bound - IntroductionBranch & Bound - n-Queens ProblemBranch & Bound - Job Sequencing ProblemBranch & Bound - 0/1 Knapsack ProblemAgain, each of these sections includes detailed videos tutorial.
