Teaching & Academics Math Network Theory

Introduction to Graph Theory and Complex Networks Analysis

Get to know the hidden structures of interconnected things and how to exploit them
New
Rating: 4.7 out of 5 (3 ratings)
210 students
Created by Alberto Calderone
Enroll now
Introduction to Graph Theory and Complex Networks Analysis
New
Rating: 4.7 out of 5 (3 ratings)
211 students
Buy now
What is Graph Theory and some basic results
What are complex networks and how to describe and analyse them
An overview on how to manipulate and analyse these structure
Two real-life examples

Requirements

  • Curiosity
  • Basic knowledge/understanding of mathematics
  • Basic knowledge/understanding of statistics
Description

Free final test to get a certificate inside. Suggested playback 1.25.

With this course you will learn what graphs are and how to use these structures to solve real life problems. In the second section of this course you will learn what complex networks are and how you can extract information from them. Finally you will see two practical examples of network analysis and some tools to enjoy graph theory and complex networks analysis.

Who this course is for:
  • Anyone willing to know how things connected together form meaningful structures
Course content
4 sections • 11 lectures • 1h 44m total length
  • Introduction to Graph Theory
    12:30
  • One Structure many Types
    14:32
  • Basic Theoretical Results and Applications
    08:23
  • Introduction to Complex Networks
    10:22
  • Description, Analysis
    09:11
  • Network Models
    16:23
  • Communities and Motifs
    08:36
  • Visualization + Robustness
    10:07
  • Exam
    00:00
  • Books, tools and programming language libraries
    07:45
  • Two examples
    06:21

Instructor
Alberto Calderone
PhD | Network Science | ML/AI/NLP | Data Science
Alberto Calderone
  • 4.7 Instructor Rating
  • 3 Reviews
  • 211 Students
  • 1 Course

Former researcher, data scientist and lifelong computer scientist. Experience in scientific research, graph theory, network science and complex networks, machine learning, data science and analysis, complex systems, algorithms design, computational linguistics, natural language processing, software development, computational biology, big data. Research Scientist. Lecturer and teaching assistant. Passionate about languages, linguistics, astronomy and astrophysics.