HomeCoursesIntroduction to Complex Network Analysis with Python

Intermediate

Introduction to Complex Network Analysis with Python

Explore complex network theory, metrics, and analysis via Python's NetworkX. Gain insights into creating, visualizing, and applying networks in fields like machine learning and data analysis.

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Overview

Content

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Complex networks are a powerful data structure capable of modeling several complex data relationships such as social media interactions, ecosystems, energy systems, and financial information. In this course, you’ll learn the basic theory behind complex networks and the metrics commonly used to analyze them. Then, you’ll learn how to create complex networks, visualize them, and calculate their analysis metrics using NetworkX, the most used Python library for complex network analysis. Finally, you’ll learn some advanced applications of complex networks, such as machine learning applications and embedding generation using complex networks. By the end of this course, you’ll have a basic understanding of what complex networks are and how you can use them in your application using Python. With this knowledge, you can generate more advanced analyses and examine data from new perspectives, improving your analytical skills.

Complex networks are a powerful data structure capable of modeling several complex data relationships such as social media inter...Show More

WHAT YOU'LL LEARN

An understanding of complex networks and how to analyze them using Python

Hands-on experience with the NetworkX Python library for complex network analysis

Familiarity with the scikit-net library to apply machine learning algorithms to complex networks

The ability to load, analyze, visualize, and infer characteristics of complex networks using Python

An understanding of complex networks and how to analyze them using Python

Content

32 Lessons11 Quizzes5 Assessments14 Challenges

Introduction to Graphs and Complex Networks

6 Lessons

Get familiar with complex networks, graph types, random graphs, and NetworkX for analysis.

Introduction to the Course

Complexity and Complex Networks

Assess Your Knowledge of Graphs and Complex Networks

Assessment

Graphs and Complex Networks in Python

4 Lessons

Get started with representing, analyzing, visualizing, and saving complex networks using Python's NetworkX library.

Network Data Representations

NetworkX Overview

Saving and Plotting Networks with NetworkX

Quiz: Graphs and Complex Networks in Python

Complex Networks Measurements

9 Lessons

Examine various centrality metrics and their applications using Python for network analysis.

What Is Centrality?

Degree

Eigenvector Centrality

The Katz Centrality

The PageRank Algorithm

The Closeness Centrality

The Betweenness Centrality

The Clustering Coefficient

Quiz: Complex Networks Measurement

Assess Your Knowledge of Complex Networks in Python

Assessment

Random Graphs and Complex Networks Models

2 Lessons

Grasp the fundamentals of small-world and scale-free network models, their properties, and generation techniques.

Small-World Networks

Scale-Free Networks

Community Detection in Complex Networks

4 Lessons

Take a closer look at community detection methods, including Louvain, sknet, and particle competition.

Community Definition

The Louvain Algorithm

Introduction to the sknet Package

Particle Competition Algorithm

Assess Your Knowledge of Network Models and Community Detection

Assessment

Similarity in Complex Networks

2 Lessons

Tackle similarity concepts in complex networks and their use in link prediction.

Similarity and Equivalence

Using Similarity for Link Prediction

Assess Your Knowledge of Similarity in Complex Networks

Assessment

Complex Network Embeddings

4 Lessons

Master the steps to generate network embeddings with DeepWalk, Node2Vec, and Graph2Vec algorithms.

Embeddings and Random Walks

The DeepWalk Algorithm

The Node2Vec Algorithm

The Graph2Vec Algorithm

Assess Your Knowledge of Network Embeddings

Assessment

Wrap Up

1 Lessons

Get familiar with essential skills in network data manipulation, community detection, and machine learning.

Conclusion

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Tiago Toledo Jr

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