This course will introduce the learner to network analysis through 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.
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This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python and Applied Machine Learning in Pytho.
What you will learn:
- Represent and manipulate networked data using the NetworkX library
- Analyze the connectivity of a network
- Measure the importance or centrality of a node in a network
- Predict the evolution of networks over time
Course 5 of 5 in the Applied Data Science with Python Specialization.
