This course is part of the Big Data Specialization

4.3
stars
1,237 ratings

Amarnath Gupta

47,400 already enrolled

Offered By

Big Data SpecializationUniversity of California San Diego

About this Course

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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.

Flexible deadlines

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Coursera Labs

Includes hands on learning projects.

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Course 5 of 6 in the

Big Data Specialization

Approx. 13 hours to complete

English

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Skills you will gain

Graph Theory
Neo4j
Analytics
Graph Database

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 5 of 6 in the

Big Data Specialization

Approx. 13 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Instructor rating

4.38/5 (65 Ratings)

Amarnath Gupta

Director, Advanced Query Processing Lab

San Diego Supercomputer Center (SDSC)

435,155 Learners

9 Courses

Offered by

University of California San Diego

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Syllabus - What you will learn from this course

Content Rating89%(3,937 ratings)

Week1

Week 1

4 minutes to complete

Welcome to Graph Analytics

4 minutes to complete

1 video (Total 4 min)

Week2

Week 2

3 hours to complete

Introduction to Graphs

Welcome! This week we will get a first exposure to graphs and their use in everyday life. By the end of the module you will be able to create a graph applying core mathematical properties of graphs, and identify the kinds of analysis questions one might be able to ask of such a graph. We hope the you will be inspired as to how graphical representations might enable you to answer new Big Data problems!

3 hours to complete

8 videos (Total 38 min), 2 readings, 2 quizzes

8 videos

What is a Graph?7mWhy Graphs?2mWhy Graphs? Example 1: Social Networking3mWhy Graphs? Example 2: Biological Networks3mWhy Graphs? Example 3: Human Information Network Analytics3mWhy Graphs? Example 4: Smart Cities2mThe Purpose of Analytics1mWhat are the impact of Big Data's V's on Graphs?12m

2 readings

What to learn in this module10mDownload Slides for this Module10m

1 practice exercise

Introduction to Graphs30m

Week3

Week 3

3 hours to complete

Graph Analytics

3 hours to complete

17 videos (Total 81 min), 3 readings, 2 quizzes

17 videos

Focusing On Graph Analytics Techniques10mPath Analytics6mThe Basic Path Analytics Question: What is the Best Path?4mApplying Dijkstra's Algorithm5mInclusion and Exclusion Constraints1mConnectivity Analytics3mDisconnecting a Graph1mConnectedness: Indegree and Outdegree3mCommunity Analytics and Local Properties7mGlobal Property: Modularity7mCentrality Analytics8mOptional Lecture 1: Bi-directional Dijkstra Algorithm2mOptional Lecture 2: Goal-directed Dijkstra Algorithm2mOptional Lecture 3: Power Law Graphs2mOptional Lecture 4: Measuring Graph Evolution3mOptional Lecture 5: Eigenvector Centrality6mOptional Lecture 6: Key Player Problems2m

3 readings

What to learn in this module10mIf this module takes a little longer... that's OK!10mDownload All Slides for Module 310m

2 practice exercises

Graph Analytics Applications30mConnectivity, Community, and Centrality Analytics30m

Week4

Week 4

4 hours to complete

Graph Analytics Techniques

Welcome to the 4th module in the Graph Analytics course. Last week, we got a glimpse of a number of graph properties and why they are important. This week we will use those properties for analyzing graphs using a free and powerful graph analytics tool called Neo4j. We will demonstrate how to use Cypher, the query language of Neo4j, to perform a wide range of analyses on a variety of graph networks.

4 hours to complete

10 videos (Total 78 min), 12 readings, 2 quizzes

10 videos

Welcome to Graph Analytics Techniques2mHands-On: Downloading, Installing, and Running Neo4j5mHands-On: Getting Started With Neo4j6mHands-On: Modifying a Graph With Neo4j7mHands-On: Importing Data Into Neo4j13mHands-On: Basic Queries in Neo4j With Cypher - Part 16mHands-On: Basic Queries in Neo4j With Cypher - Part 26mHands-On: Path Analytics in Neo4j Using Cypher - Part 18mHands-On: Path Analytics in Neo4j Using Cypher - Part 211mHands-On: Connectivity Analytics in Neo4j With Cypher9m

12 readings

About the Supplementary Resources10mDownloading, Installing, and Running Neo4j - Supplementary Resources10mGetting Started With Neo4j - Supplementary Resources10mAdding to and Modifying a Graph - Supplementary Resources10mDownload datasets used in this Graph Analytics with Neo4j10mImporting Data Into Neo4j - Supplementary Resources10mFAQ10mBasic Queries in Neo4j With Cypher - Supplementary Resources10mPath Analytics in Neo4j With Cypher - Supplementary Resources10mConnectivity Analytics in Neo4j with Cypher - Supplementary Resources10mAssignment: Practicing Graph Analytics in Neo4j With Cypher10mDownload All Neo4j Supplementary Resources (PDFs)10m

2 practice exercises

Quiz: Graph Analytics With Neo4j30mAssessment Questions on 'Practicing Graph Analytics in Neo4j With Cypher'30m

Reviews

4.3

237 reviews

5 stars
55.53%
4 stars
26.75%
3 stars
11.31%
2 stars
3.55%
1 star
2.82%

TOP REVIEWS FROM GRAPH ANALYTICS FOR BIG DATA

by STAug 12, 2020

The week 5 module was difficult to digest completely, it could be made better with better explanations of what is happening

by KDMay 22, 2020

The course content is pretty good but the instructions provided are not up to the mark nor are they updated hence I personally faced a lot of troubles during my time of completion

by KMDec 16, 2017

Got an amazing introduction to Graph Analytics in Big Data. Technical issues with Neo4J made this course a little more challenging than necessary. But the introduction to Spark GraphX was invaluable.

by JCDec 8, 2018

Graphs are quite interesting and in many cases offer a better representation than relational databases.

One can gain lots of insights looking at graphs.

View all reviews

About the Big Data Specialization

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.

********* Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Graph Analytics for Big Data

About this Course

Skills you will gain