This course is part of the Big Data Specialization

4.3
stars
1,179 ratings

Amarnath Gupta

42,081 already enrolled

Offered By

Big Data SpecializationUniversity of California San Diego

About this Course

46,211 recent views

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

Reset deadlines in accordance to your schedule.

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

Approx. 13 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish

Skills you will gain

Graph TheoryNeo4jAnalyticsGraph 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.

Course 5 of 6 in the

Big Data Specialization

Approx. 13 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish

Instructor

Instructor rating

4.4/5 (49 Ratings)

Amarnath Gupta

Director, Advanced Query Processing Lab

San Diego Supercomputer Center (SDSC)

398,730 Learners

9 Courses

Offered by

University of California San Diego

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.

Syllabus - What you will learn from this course

Content Rating89%(3,675 ratings)

Week

Week 1

4 minutes to complete

Welcome to Graph Analytics

Meet your instructor, Amarnath Gupta and learn about the course objectives.

4 minutes to complete

1 video (Total 4 min)

Week

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?7m

Why Graphs?2m

Why Graphs? Example 1: Social Networking3m

Why Graphs? Example 2: Biological Networks3m

Why Graphs? Example 3: Human Information Network Analytics3m

Why Graphs? Example 4: Smart Cities2m

The Purpose of Analytics1m

What are the impact of Big Data's V's on Graphs?12m

2 readings

What to learn in this module10m

Download Slides for this Module10m

1 practice exercise

Introduction to Graphs30m

Week

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 Techniques10m

Path Analytics6m

The Basic Path Analytics Question: What is the Best Path?4m

Applying Dijkstra's Algorithm5m

Inclusion and Exclusion Constraints1m

Connectivity Analytics3m

Disconnecting a Graph1m

Connectedness: Indegree and Outdegree3m

Community Analytics and Local Properties7m

Global Property: Modularity7m

Centrality Analytics8m

Optional Lecture 1: Bi-directional Dijkstra Algorithm2m

Optional Lecture 2: Goal-directed Dijkstra Algorithm2m

Optional Lecture 3: Power Law Graphs2m

Optional Lecture 4: Measuring Graph Evolution3m

Optional Lecture 5: Eigenvector Centrality6m

Optional Lecture 6: Key Player Problems2m

3 readings

What to learn in this module10m

If this module takes a little longer... that's OK!10m

Download All Slides for Module 310m

2 practice exercises

Graph Analytics Applications30m

Connectivity, Community, and Centrality Analytics30m

Week

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 Techniques2m

Hands-On: Downloading, Installing, and Running Neo4j5m

Hands-On: Getting Started With Neo4j6m

Hands-On: Modifying a Graph With Neo4j7m

Hands-On: Importing Data Into Neo4j13m

Hands-On: Basic Queries in Neo4j With Cypher - Part 16m

Hands-On: Basic Queries in Neo4j With Cypher - Part 26m

Hands-On: Path Analytics in Neo4j Using Cypher - Part 18m

Hands-On: Path Analytics in Neo4j Using Cypher - Part 211m

Hands-On: Connectivity Analytics in Neo4j With Cypher9m

12 readings

About the Supplementary Resources10m

Downloading, Installing, and Running Neo4j - Supplementary Resources10m

Getting Started With Neo4j - Supplementary Resources10m

Adding to and Modifying a Graph - Supplementary Resources10m

Download datasets used in this Graph Analytics with Neo4j10m

Importing Data Into Neo4j - Supplementary Resources10m

FAQ10m

Basic Queries in Neo4j With Cypher - Supplementary Resources10m

Path Analytics in Neo4j With Cypher - Supplementary Resources10m

Connectivity Analytics in Neo4j with Cypher - Supplementary Resources10m

Assignment: Practicing Graph Analytics in Neo4j With Cypher10m

Download All Neo4j Supplementary Resources (PDFs)10m

2 practice exercises

Quiz: Graph Analytics With Neo4j30m

Assessment Questions on 'Practicing Graph Analytics in Neo4j With Cypher'30m

Reviews

4.3

224 reviews

5 stars
55.37%
4 stars
26.58%
3 stars
11.60%
2 stars
3.64%
1 star
2.79%

TOP REVIEWS FROM GRAPH ANALYTICS FOR BIG DATA

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 JTOct 25, 2016

This course was excellent as an introduction to Graph Analytics and using Neo4j. Not only did I learn a lot, I've been given tasks related to what I've learned in this course after finishing it.

by JAOct 27, 2018

I found a new love in this course Neo4j. Graphs are really powerful. You should expect a very intensive theoretical and hands-on knowledge to takeaway from this course. Think like a vertex ....

by AKNov 22, 2020

Interesting course but Week 5 was exceptionally buggy. Is that on purpose to help us learn about small errors that can creep in OR has the course not been updated for quite some time?

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, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.

Graph Analytics for Big Data

About this Course

Skills you will gain

Instructor

Amarnath Gupta

Offered by

University of California San Diego

Syllabus - What you will learn from this course

Week 1

Welcome to Graph Analytics

Week 2

Introduction to Graphs

Week 3

Graph Analytics

Week 4

Graph Analytics Techniques

Week 5

Computing Platforms for Graph Analytics

Reviews

TOP REVIEWS FROM GRAPH ANALYTICS FOR BIG DATA

About the Big Data Specialization

Frequently Asked Questions

Start or advance your career

Browse popular topics

Upskill your team

Earn a degree or certificate online

Coursera

Community

More

Graph Analytics for Big Data

About this Course

Skills you will gain

Instructor

Amarnath Gupta

Offered by

University of California San Diego

Syllabus - What you will learn from this course

Week 1

Welcome to Graph Analytics

Week 2

Introduction to Graphs

Week 3

Graph Analytics

Week 4

Graph Analytics Techniques

Week 5

Computing Platforms for Graph Analytics

Reviews

TOP REVIEWS FROM GRAPH ANALYTICS FOR BIG DATA

About the Big Data Specialization

Frequently Asked Questions

Coursera Footer

Start or advance your career

Browse popular topics

Upskill your team

Earn a degree or certificate online

Coursera

Community

More