Learn Graphs and Social Network Analytics Using Python

This course is absolutely designed for beginners , graph enthusiast ready to analyze the world using graphs
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  • Lectures 66
  • Length 6.5 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
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    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 12/2015 English

Course Description

BRAND NEW COURSE IS HERE ! Learn Graphs and Social Network Analytics .Become a graph and social analyst today. This is a comprehensive course , simple and straight forward for python enthusiast and those with little python background. You want to learn about how to draw graphs and analyze them, this is the course for you. This course will contain some quizzes, test and some homework assignments, as well as some real world assignment projects. There is over 55 lectures and about 6hours to complete the course. This course comes with live coding screenshots using iPython Notebook .Below is the list of the course summary

- Overivew of networkX

- Install networkX module and iPython Notebooks

- Create nodes

- Add edges to nodes

- Getting attributes from a graph

- Manipulate your graphs ie.; remove nodes /edges

- Create DiGraphs/MultiGraphs/MultiDiGraphs

- Graph Generators

- Graph metrics ; shortest path/clustering coefficient

- Define functions

- Visualize graphs

- Calculate nodes/degree/centrality metrics

- Some random graphs

- Small famous graphs

- Reading and writing graph files

- Social network analysis

- Subgraphs

- Facebook Social Network Analysis

Course goals :

-At the end of the course students should be able to learn some basics of graph theory

- Students should be able to analyze Facebook social networks

- Students should take the simple quizzes

- Students should know what is directed and undirected graphs

- Students should be able to visualize graphs using different graph plots

- You can use this course to analyze the world as a network

- Everything in this world is now connected

- Extract useful information from graphs

Life time access to the course. What are you waiting for? Learn practical graph and social network analytics today that would improve your career and increase your knowledge.

What are the requirements?

  • Basic programming knowledge in python or other language
  • Access to computer and with an internet
  • Fundamentals of Graph Theory

What am I going to get from this course?

  • Create graphs using NetworkX package
  • Create nodes of a graph
  • Create edges of a graph
  • Determine the attributes of a node and edges
  • Analyze social networks like Facebook and Twitter
  • Students will learn more about properties of a graph
  • Learn about Clustering coefficient , Betweenness centrality, degree centrality etc
  • Learn about Connected graphs, Bipartite graphs, etc
  • Learn about the types of graphs used for social network analysis

What is the target audience?

  • Beginners who have never programmed in python before
  • Students who are Graph Enthusiast
  • Intermediate python programmers who want to level up their skills
  • Students who want to analyze social networks like Facebook and Twitter
  • Mathematics students who wants to apply their knowledge in Graph Theory

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.

Curriculum

Section 1: Introduction
05:19

Introduction of the course ; learn graphs and social network analytics using python

01:12

my github

Section 2: Overview of networkX
07:38

An overview of networkx module in python

4 questions

Basic graph theory

04:30

introduction to network Basics; nodes and edges

NetworkX Basics
7 questions
Section 3: Installation of networkX and iPython Notebooks
07:43

how to Install networkX and iPython Notebooks , how to download networkX and iPython notebooks

Installation of iPython Notebook
1 question
Section 4: Creating nodes using networkX
05:12

how to Create Nodes using python with networkX modules

Section 5: Adding edges to graphs
05:36

how to Add Edges to a graph using networkX modules in python

Section 6: Getting graph properties
08:08

how to get graph properties using networkX

Section 7: Node Manipulation
04:58

how to Node manipulate edges and nodes using networkx with python

Section 8: Adding attributes to graphs
05:12

how to add attributes to graphs using networkX module with python

05:08

how to add attributes to graphs using networkX module with python

Section 9: Adding edge attributes to graphs
06:47

how to Add Edge Attributes to graphs using networkx modules with python

04:54

how to Add Edge Attributes to graphs using networkx modules with python

Section 10: Creating DiGraphs
09:05

how to Create DiGraphs with networkX using python

04:52

how to Create DiGraphs with networkX using python

Section 11: Creating MultiGraphs
08:58

how to Create MultiGraphs with networkX using python

Section 12: Creating MultiDiGraphs
09:03

how to Create MultiDiGraphs with networkX using python

Section 13: Graph Generators
07:24

how to create Graph Generators with networkX using python

06:28

how to create Graph Generators with networkX using python

Section 14: Graph Metrics
06:51

how to calculate Shortest Path in a graph using networkx and python

04:27

how to calculate Clustering Coeficient using networkX and python

Section 15: Defining Functions
03:20

how to Define Functions for graphs with networkX using python

04:09

how to Define Functions for graphs with networkX using python

04:35

Define Function Nodes

04:28

Delete nodes from a graph

04:40

Delete edges from a graph

05:01

node size and node colors

05:36

creating edge colors in a graph

Section 16: Graph Visualizations
05:22

Drawing Graph Images using networkX

04:47

Drawing Circular Graph using networkX

04:07

Draw bar graph using the values of the betweenness centrality

Section 17: Nodes , Degrees and Centrality Metrics
03:57

Calculate Nodes, Degrees and Centrality

Section 18: Random Graphs
06:46

how to create Grid Graphs

03:19

how to create Circular Tree graphs

08:52

how to draw Bipartite graphs using networkX and python

06:24

learn how to create Random graphs

07:02

Drawing a house graph

Section 19: Small Famous Graphs
04:48

what is small famous graphs

09:05

small famous graphs with networkX

11:57

Learn to create Classical graphs

Section 20: Reading and writing graph files
04:58

learn how to write graph files to disk using networkX and python

02:16

learn how to read graph files to disk using networkX and python

05:12

learn how to Read and Writing Edgelist using networkX and python

03:19

how to Read files using Open Function with networkX and python

03:36

Reading edge list files

Section 21: Social Network Analysis
10:27

Social network analysis using networkX and python

08:21

Social network analysis using networkX and python

05:30

Social network analysis using networkX and python

05:17

Social network analysis using networkX and python

05:12

Social network analysis using networkX and python

04:34

Social network analysis using networkX and python

08:21

Social network analysis using networkX and python

Section 22: Subgraphs
03:32

learn how to create Subgraphs with networkX and python

04:58

Number of triangles in a graph

Section 23: Facebook Social Network Analysis
09:37

Learn Facebook Network Analysis using networkX and python

07:13

Learn Facebook Network Analysis using networkX and python

Section 24: Twitter Social Network Analysis
07:08

how to create twitter apps account

05:28

How to connect to twitter api

05:33

How to get data from twitter using the API

06:02

How to work with retweets data set

09:14

Drawing networkx layouts

04:08

making networks with twitter data

03:40

graphing degree centrality

05:24

creating digraphs with twitter data

05:48

graphing in and out degree centralities

Section 25: Conclusions
Thank you & Good Bye
01:20

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Instructor Biography

Theophilus Siameh, SAS Programmer, Data Analyst, and Predictive Modeler

I'm SAS Programmer, Data Analyst, Predictive Modeler, Graph Analyst and building Android Mobile Applications . I'm currently in a Masters degree program at East Tennessee State University, Johnson City ,Tennessee . Over the course of my career I have developed a skill set in analyzing data, specifically using Python and a variety of modules and libraries. I hopes to use this experience in teaching and data science to help other people learn the power of the Python programming language and its ability to analyze data,and graph as well as present the data in clear and beautiful visualizations.

I also have the following SAS Certifications :

SAS Certified Base Programmer for SAS 9 Certified 02/04/2015

SAS Certified Clinical Trials Programmer Using SAS 9 Certified 06/12/2015

SAS Certified Advanced Programmer for SAS 9 Certified 04/29/2015

SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Certified 08/25/2015

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