Applied Social Network Analysis in Python
- Offered byCoursera
Applied Social Network Analysis in Python at Coursera Overview
Duration | 29 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Applied Social Network Analysis in Python at Coursera Highlights
- This Course Plus the Full Specialization.
- Shareable Certificates.
- Graded Programming Assignments.
Applied Social Network Analysis in Python at Coursera Course details
- 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.
Applied Social Network Analysis in Python at Coursera Curriculum
Why Study Networks and Basics on NetworkX
Networks: Definition and Why We Study Them
Network Definition and Vocabulary
Node and Edge Attributes
Bipartite Graphs
TA Demonstration: Loading Graphs in NetworkX
Course Syllabus
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Notice for Auditing Learners: Assignment Submission
Module 1 Quiz
Network Connectivity
Clustering Coefficient
Distance Measures
Connected Components
Network Robustness
TA Demonstration: Simple Network Visualizations in NetworkX
Module 2 Quiz
Influence Measures and Network Centralization
Degree and Closeness Centrality
Betweenness Centrality
Basic Page Rank
Scaled Page Rank
Hubs and Authorities
Centrality Examples
Module 3 Quiz
Network Evolution
Preferential Attachment Model
Small World Networks
Link Prediction
Power Laws and Rich-Get-Richer Phenomena (Optional)
The Small-World Phenomenon (Optional)
Post-Course Survey
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Module 4 Quiz
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