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.
Graph Analytics for Big Data
Graph Analytics for Big Data
This course is part of Big Data Specialization
Instructor: Amarnath Gupta
Sponsored by Coursera Learning Team
53,525 already enrolled
Gain insight into a topic and learn the fundamentals.
4.3
(1,267 reviews)
11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
89%
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Assessments
6 assignments
Taught in English
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This course is part of the Big Data Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
Meet your instructor, Amarnath Gupta and learn about the course objectives.
What's included
1 video1 reading
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!
What's included
8 videos2 readings1 assignment1 peer review2 discussion prompts
What's included
17 videos3 readings2 assignments2 discussion prompts
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.
What's included
7 videos9 readings2 assignments
In the last two modules we have learned about graph analytics and graph data management. This week we will study how they come together. There are programming models and software frameworks created specifically for graph analytics. In this module we'll give an introductory tour of these models and frameworks. We will learn to implement what you learned in Week 2 and build on it using GraphX and Giraph.
What's included
11 videos6 readings1 assignment
Instructor
Instructor ratings
4.4 (70 ratings)Offered by
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4.3
1,267 reviews
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Showing 3 of 1267
LK
5
Reviewed on Jul 20, 2017
Gives wonderful overview and hands on experience Graph analytic. Course Contents were very crisp and pretty comprehensive for a novice.
JA
5
Reviewed on Oct 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 ....
KD
4
Reviewed on May 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
Recommended if you're interested in Data Science
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