Udemy - Network Analytics and Visualization in Python

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Udemy - Network Analytics and Visualization in Python (Size: 1.5 GB)
  1 -1.pdf 31.6 MB
  1 -Course outro.mp4 18.4 MB
  1 -Section intro.mp4 14.9 MB
  1 -python_env_details.txt 16.8 KB
  1 -requirements.txt 16.7 KB
  2 -13.ipynb 652.4 KB
  2 -2.ipynb 4.3 KB
  2 -7.ipynb 464.4 KB
  2 -Creating Your First Graph.mp4 21 MB
  2 -Generating Synthetic Networks.mp4 83.6 MB
  2 -Network Layouts.mp4 71.8 MB
  3 -14.ipynb 3.1 MB
  3 -14_witcher_network.gexf 513.6 KB
  3 -3.ipynb 77 KB
  3 -8.ipynb 437.4 KB
  3 -Drawing Your First Graphs.mp4 20.5 MB
  3 -Network Centralities.mp4 132.9 MB
  3 -Read and Explore a Real Network.mp4 258.2 MB
  4 -14_manhattan_network.gexf 112.7 KB
  4 -15.ipynb 1.3 MB
  4 -15_nobel_demo.gexf 91.5 KB
  4 -15_pypackages.gexf 58.5 KB
  4 -15_witcher_network.gexf 513.6 KB
  4 -4.ipynb 107.8 KB
  4 -9.ipynb 83.9 KB
  4 -Comparative Network Analytics.mp4 332.9 MB
  4 -Creating Different Types of Graphs.mp4 76.6 MB
  4 -Network Statistics.mp4 64.1 MB
  5 -10.ipynb 63.4 KB
  5 -16.ipynb 8.5 KB
  5 -16_PyhtonPackages.gephi 139.3 KB
  5 -16_edges_updates.csv 27 KB
  5 -16_nodes_updated.csv 2 KB
  5 -5.ipynb 129.7 KB
  5 -5_dummy.gexf 2.7 KB
  5 -5_edges.csv 921.6 B
  5 -Create Graph From Data.mp4 55.6 MB
  5 -Network Modularity.mp4 75.7 MB
  5 -Python and Gephi.mp4 121.3 MB
  6 -11.ipynb 59.5 KB
  6 -Network Visualization in Python.mp4 59.8 MB
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 45 total files

Description


Network Analytics and Visualization in Python

https://WebToolTip.com

Published 2/2025
Created by Milan Janosov
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 17 Lectures ( 2h 59m ) | Size: 1.5 GB

From Graph Creation to Advanced Network Analytics and Visualization using Python

What you'll learn
Build and Analyze Networks in Python – Create, manipulate, and analyze real-world networks using Python
Master Key Network Metrics and Algorithms – Apply centrality measures, modularity, clustering, and other graph-based techniques to uncover characterize graphs
Develop Practical Visualization and Analysis Skills – Use Python to create interactive and informative network visualizations for data-driven decision
Design Network Analytical Pipelines – Learn the complete workflow of network analysis

Requirements
Functional, beginner level Python programing
Basic knowledge of network science concepts

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