Applied Social Network Analysis in Python

开始时间: 12/19/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 计算机科学

大学或机构: CourseraNew



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This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week introduces the concept of connectivity and network robustness. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem. This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python.

Python中的应用社交网络分析:本课程将通过使用NetworkX库的教程向学习者介绍网络分析。本课程首先了解什么是网络分析以及为什么我们可以将现象建模为网络的动机。第二周介绍了连接性和网络健壮性的概念。第三周将探讨测量网络中节点重要性或中心性的方法。最后一周将探讨网络随时间的演变,并介绍网络生成和链路预测问题的模型。 本课程应在以下课程之后进行:Python中的数据科学导论,应用绘图,制图和绘图。 Python中的数据表示和Python中的应用机器学习。


Module One introduces you to different types of networks in the real world and why we study them. You'll learn about the basic elements of networks, as well as different types of networks. You'll also learn how to represent and manipulate networked data using the NetworkX library. The assignment will give you an opportunity to use NetworkX to analyze a networked dataset of employees in a small company.



This course will introduce the learner to network analysis through the NetworkX library. The course


社交网络分析 数据科学 Python Python社交网络分析 Python社交网络分析应用