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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/trees-graphs-basics
课程评论：没有评论
课程名称：树与图：基础 概述：本课程涵盖树数据结构的基本算法、二叉搜索树、自平衡树、图数据结构以及图的基本遍历算法。课程还将介绍高级主题，如用于空间数据的kd树及其相关算法。树与图：基础课程可作为科罗拉多大学博尔德分校的数据科学硕士（MS-DS）学位的一部分，在Coursera平台上提供。该学位属于跨学科课程，结合了应用数学、计算机科学、信息科学等多个部门的教师资源。MS-DS课程具有基于表现的入学条件，且无需申请流程，非常适合在计算机科学、信息科学、数学和统计学领域有广泛本科教育背景或专业经验的个人。更多信息请访问 https://www.coursera.org/degrees/master-of-science-data-science-boulder。 教学大纲： 1. **二叉搜索树与树上的算法** - 本模块将学习二叉搜索树及其基本算法，了解二叉搜索树的平衡问题，并研究解决平衡二叉搜索树的方案，如红黑树。 2. **图的基础知识与图的遍历** - 本模块将学习图及其各种基本算法，如深度优先遍历/广度优先遍历、寻找强连通分量和拓扑排序。 3. **并查集数据结构与生成树算法** - 包括具有秩压缩的并查集数据结构，生成树及其性质，普里姆算法与克鲁斯克尔算法用于寻找最小生成树。 4. **最短路径算法** - 本模块将涉及最短路径问题的基础知识，贝尔曼-福特算法、迪杰斯特拉算法，以及针对所有点的最短路径问题的算法（弗洛伊德-华尔肖算法）。
Name:Binary Search Trees and Algorithms on Trees
Description:In this module, you will learn about binary search trees and basic algorithms on binary search trees. We will also become familiar with the problem of balancing in binary search trees and study some solutions for balanced binary search trees such as Red-Black Trees.
Name:Basics of Graphs and Graphs Traversals
Description:In this module, you will learn about graphs and various basic algorithms on graphs such as depth first/breadth first traversals, finding strongly connected components, and topological sorting.
Name:Union-Find Data Structures and Spanning Tree Algorithms
Description:Union Find Data-structure with rank compression. Spanning trees and properties of spanning trees. Prim’s algorithm for finding minimal spanning trees. Kruskal’s algorithm for finding minimal spanning trees.
Name:Shortest Path Algorithms
Description:In this module, you will learn about: Shortest Path Problem: Basics. Bellman-Ford Algorithm for single source shortest path. Dijkstra’s algorithm. Algorithms for all-pairs shortest path problem (Floyd-Warshall Algorithm)
Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data. Trees and Graphs: Basics can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
