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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-java/
课程评论：没有评论
Coursera 课程《Java 数据结构与算法深入解析》总结： 本课程全面深入地讲解了数据结构和算法的基础知识，并结合 Java 语言进行实现。课程内容结构清晰，理论讲解与代码实现相结合，旨在帮助学习者扎实掌握 DSA 核心概念。 **课程涵盖的主要内容包括：** * **数据结构与算法基础：** 介绍基本数据结构和算法的原理。 * **算法分析：** 重点讲解 Big O 符号、时间复杂度和空间复杂度分析，帮助理解算法的效率。 * **递归：** 深入探讨递归的概念及其算法分析。 * **核心数据结构：** * 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) * 优先队列和堆 (Priority Queues and Heaps) * 哈希表 (Hashing) * **图论：** * 图 (Graphs) * 图遍历算法 (Graph Traversal Algorithms) * **高级算法主题：** * **集合与不相交集合 (Sets and Disjoint Sets)** * **分治法 (Divide and Conquer)：** 包括二分查找、最大最小值查找、归并排序、快速排序、选择算法、Strassen 矩阵乘法、最近点对、凸包等。 * **贪心算法 (Greedy Method)：** 包括背包问题、带截止日期的作业排序、最小生成树 (Prim & Kruskal)、树上的最优存储、最优归并模式、单源最短路径 (Dijkstra) 等。 * **动态规划 (Dynamic Programming)：** 包括多阶段图、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、旅行商问题等。 * **回溯法 (Backtracking)：** 包括 N 皇后问题、子集和问题、图着色问题、哈密顿回路问题、0/1 背包问题等。 * **分支限界法 (Branch & Bound)：** 包括 N 皇后问题、作业排序问题、0/1 背包问题等。 每部分内容均包含详细的视频教程，通过理论到实践的讲解，帮助学习者全面理解并熟练运用各种数据结构和算法。
This course will help you in better understanding of the basics of Data Structures and how algorithms are implemented in Java. This course consists of Videos which covers the theory concepts + implementation in Java. 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.
