Graph Analytics for Big Data
- Offered byCoursera
Graph Analytics for Big Data at Coursera Overview
Duration | 13 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Graph Analytics for Big Data at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 5 of 6 in the Big Data Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Approx. 13 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish
Graph Analytics for Big Data at Coursera Course details
- Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data.
- After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects.
Graph Analytics for Big Data at Coursera Curriculum
Welcome to Graph Analytics
Welcome to Graph Analytics for Big Data
Introduction to Graphs
What is a Graph?
Why Graphs?
Why Graphs? Example 1: Social Networking
Why Graphs? Example 2: Biological Networks
Why Graphs? Example 3: Human Information Network Analytics
Why Graphs? Example 4: Smart Cities
The Purpose of Analytics
What are the impact of Big Data's V's on Graphs?
What to learn in this module
Download Slides for this Module
Introduction to Graphs
Graph Analytics
Focusing On Graph Analytics Techniques
Path Analytics
The Basic Path Analytics Question: What is the Best Path?
Applying Dijkstra's Algorithm
Inclusion and Exclusion Constraints
Connectivity Analytics
Disconnecting a Graph
Connectedness: Indegree and Outdegree
Community Analytics and Local Properties
Global Property: Modularity
Centrality Analytics
Optional Lecture 1: Bi-directional Dijkstra Algorithm
Optional Lecture 2: Goal-directed Dijkstra Algorithm
Optional Lecture 3: Power Law Graphs
Optional Lecture 4: Measuring Graph Evolution
Optional Lecture 5: Eigenvector Centrality
Optional Lecture 6: Key Player Problems
What to learn in this module
If this module takes a little longer... that's OK!
Download All Slides for Module 3
Graph Analytics Applications
Connectivity, Community, and Centrality Analytics
Graph Analytics Techniques
Welcome to Graph Analytics Techniques
Hands-On: Downloading, Installing, and Running Neo4j
Hands-On: Getting Started With Neo4j
Hands-On: Modifying a Graph With Neo4j
Hands-On: Importing Data Into Neo4j
Hands-On: Basic Queries in Neo4j With Cypher - Part 1
Hands-On: Basic Queries in Neo4j With Cypher - Part 2
Hands-On: Path Analytics in Neo4j Using Cypher - Part 1
Hands-On: Path Analytics in Neo4j Using Cypher - Part 2
Hands-On: Connectivity Analytics in Neo4j With Cypher
About the Supplementary Resources
Downloading, Installing, and Running Neo4j - Supplementary Resources
Getting Started With Neo4j - Supplementary Resources
Adding to and Modifying a Graph - Supplementary Resources
Download datasets used in this Graph Analytics with Neo4j
Importing Data Into Neo4j - Supplementary Resources
FAQ
Basic Queries in Neo4j With Cypher - Supplementary Resources
Path Analytics in Neo4j With Cypher - Supplementary Resources
Connectivity Analytics in Neo4j with Cypher - Supplementary Resources
Assignment: Practicing Graph Analytics in Neo4j With Cypher
Download All Neo4j Supplementary Resources (PDFs)
Quiz: Graph Analytics With Neo4j
Assessment Questions on 'Practicing Graph Analytics in Neo4j With Cypher'
Computing Platforms for Graph Analytics
Introduction: Large Scale Graph Processing
A Parallel Programming Model for Graphs
Pregel: The System That Changed Graph Processing
Giraph and GraphX
Beyond Single Vertex Computation
Introduction to GraphX: Hands-On Demonstrations
Hands On: Building a Graph
Hands On: Building a Degree Histogram
Hands On: Plot the Degree Histogram
Hands On: Network Connectedness and Clustering Components
Hands On: Joining Graph Datasets
Datasets and Libraries for Example of Analytics Hands On
Download all of the readings for this section as a PDF
Hands On: Building a Graph Reading
Hands On: Building a Degree Histogram Reading
Hands On: Plot the Degree Histogram Reading
Hands On: Network Connectedness and Clustering Components Reading
Hands On: Joining Graph Datasets Reading
Using GraphX
Graph Analytics for Big Data at Coursera Admission Process
Important Dates
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