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October 7, 2024
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This course is part of Big Data Specialization
Instructor: Amarnath Gupta
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(1,267 reviews)
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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.
Meet your instructor, Amarnath Gupta and learn about the course objectives.
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!
8 videos2 readings1 assignment1 peer review2 discussion prompts
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.
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.
11 videos6 readings1 assignment
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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.
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École Polytechnique Fédérale de Lausanne
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Reviewed on Oct 4, 2018
Great course!!! excellent information, instructions and examples (including some troubleshooting that helps us to learn things simulating everyday challenges).
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 ....
Reviewed on May 4, 2017
This is one of the toughest and most interesting course at it deals with big data in graph database. Highly recommend this course to those who wants to know graph database.
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