About this Course
4.2
750개의 평가
151개의 리뷰

다음의 5/6개 강좌

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

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완료하는 데 약 15시간 필요

권장: 4 Weeks, 3-5 hours/week...

영어

자막: 영어

귀하가 습득할 기술

Graph TheoryNeo4jAnalyticsGraph Database

다음의 5/6개 강좌

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

탄력적인 마감일

일정에 따라 마감일을 재설정합니다.

완료하는 데 약 15시간 필요

권장: 4 Weeks, 3-5 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 4분 필요

Welcome to Graph Analytics

Meet your instructor, Amarnath Gupta and learn about the course objectives....
1 video (Total 4 min)
2
완료하는 데 3시간 필요

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!...
8 videos (Total 38 min), 2 readings, 2 quizzes
8개의 동영상
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
2개의 읽기 자료
What to learn in this module10m
Download Slides for this Module10m
1개 연습문제
Introduction to Graphs24m
3
완료하는 데 3시간 필요

Graph Analytics

...
17 videos (Total 81 min), 3 readings, 2 quizzes
17개의 동영상
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
3개의 읽기 자료
What to learn in this module10m
If this module takes a little longer... that's OK!10m
Download All Slides for Module 310m
2개 연습문제
Graph Analytics Applications34m
Connectivity, Community, and Centrality Analytics38m
4
완료하는 데 4시간 필요

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. ...
10 videos (Total 78 min), 12 readings, 2 quizzes
10개의 동영상
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
12개의 읽기 자료
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
2개 연습문제
Quiz: Graph Analytics With Neo4j18m
Assessment Questions on 'Practicing Graph Analytics in Neo4j With Cypher'18m
5
완료하는 데 2시간 필요

Computing Platforms for Graph Analytics

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 videos (Total 65 min), 7 readings, 1 quiz
11개의 동영상
A Parallel Programming Model for Graphs11m
Pregel: The System That Changed Graph Processing7m
Giraph and GraphX9m
Beyond Single Vertex Computation5m
Introduction to GraphX: Hands-On Demonstrations3m
Hands On: Building a Graph7m
Hands On: Building a Degree Histogram5m
Hands On: Plot the Degree Histogram2m
Hands On: Network Connectedness and Clustering Components5m
Hands On: Joining Graph Datasets5m
7개의 읽기 자료
Datasets and Libraries for Example of Analytics Hands On10m
Download all of the readings for this section as a PDF10m
Hands On: Building a Graph Reading10m
Hands On: Building a Degree Histogram Reading10m
Hands On: Plot the Degree Histogram Reading10m
Hands On: Network Connectedness and Clustering Components Reading10m
Hands On: Joining Graph Datasets Reading10m
1개 연습문제
Using GraphX8m
4.2
151개의 리뷰Chevron Right

50%

이 강좌를 수료한 후 새로운 경력 시작하기

32%

이 강좌를 통해 확실한 경력상 이점 얻기

최상위 리뷰

대학: KMDec 17th 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.

대학: JTOct 26th 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.

강사

Avatar

Amarnath Gupta

Director, Advanced Query Processing Lab
San Diego Supercomputer Center (SDSC)

캘리포니아 샌디에고 대학교 정보

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....

빅 데이터 전문 분야 정보

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....
빅 데이터

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