Algorithmic Thinking (Part 2)

所在平台: Coursera

课程主页: https://www.coursera.org/learn/algorithmic-thinking-2

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课程简介

课程名称:算法思维(第二部分) 概述:经验丰富的计算机科学家在超越特定编程语言的抽象层面上分析和解决计算问题。本课程旨在训练学生掌握“算法思维”的数学概念和过程,使他们能够构建更简单、更高效的计算问题解决方案。在本课程的第二部分,我们将学习高级算法技术,如分治法和动态规划。学生将实现多种算法,这些算法结合了所学的技术,并使用这些算法分析两个大型真实数据集。课程的主要重点在于理解算法与被分析数据集结构之间的互动关系。 完成本课程后,学生将具备分析、设计和编写解决各种计算问题的算法和编程技能。虽然本课程将Python作为实践算法思维的工具,但您所学到的概念超越了特定的编程语言。 课程大纲: - 模块3 - 核心材料:排序、搜索、大O符号、主定理 - 模块3 - 项目与应用:最近点对、点的聚类、聚类算法的比较 - 模块4 - 核心材料:动态规划、动态规划算法的运行时间、本地和全局序列比对 - 模块4 - 项目与应用:序列比对的计算、基因组学和文本比较的应用

课程大纲

Name:Module 3 - Core Materials

Description:Sorting, searching, big-O notation, the Master Theorem

Name:Module 3 - Project and Application

Description:Closest pairs of points, clustering of points, comparison of clustering algorithms

Name:Module 4 - Core Materials

Description:Dynamic programming, running time of DP algorithms, local and global sequence alignment

Name:Module 4 - Project and Application

Description:Computation of sequence alignments, applications to genomics and text comparison

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课程详情

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems. In part 2 of this course, we will study advanced algorithmic techniques such as divide-and-conquer and dynamic programming. As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Once students have completed this class, they will have both the mathematical and programming skills to analyze, design, and program solutions to a wide range of computational problems. While this class will use Python as its vehicle of choice to practice Algorithmic Thinking, the concepts that you will learn in this class transcend any particular programming language.

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