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.
oferecido por
Programa de cursos integrados Big DataBig DataUniversidade da Califórnia, San DiegoInformações sobre o curso
65,602 visualizações recentes
Resultados de carreira do aprendiz
42%
comecei uma nova carreira após concluir estes cursos
28%
consegui um benefício significativo de carreira com este curso
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 5 de 6 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Aprox. 12 horas para completar
Inglês
Legendas: Inglês, Coreano
Habilidades que você terá
Graph TheoryNeo4jAnalyticsGraph Database
Resultados de carreira do aprendiz
42%
comecei uma nova carreira após concluir estes cursos
28%
consegui um benefício significativo de carreira com este curso
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 5 de 6 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Aprox. 12 horas para completar
Inglês
Legendas: Inglês, Coreano
oferecido por
Universidade da Califórnia, 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.
Programa - O que você aprenderá com este curso
4 minutos para concluir
Welcome to Graph Analytics
Meet your instructor, Amarnath Gupta and learn about the course objectives.
4 minutos para concluir
1 vídeo (Total 4 mín.)
1 vídeos
3 horas para concluir
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 horas para concluir
8 vídeos (Total 38 mín.), 2 leituras, 2 testes
8 videos
What is a Graph?7min
Why Graphs?2min
Why Graphs? Example 1: Social Networking3min
Why Graphs? Example 2: Biological Networks3min
Why Graphs? Example 3: Human Information Network Analytics3min
Why Graphs? Example 4: Smart Cities2min
The Purpose of Analytics1min
What are the impact of Big Data's V's on Graphs?12min
2 leituras
What to learn in this module10min
Download Slides for this Module10min
1 exercício prático
Introduction to Graphs24min
3 horas para concluir
Graph Analytics
3 horas para concluir
17 vídeos (Total 81 mín.), 3 leituras, 2 testes
17 videos
Path Analytics6min
The Basic Path Analytics Question: What is the Best Path?4min
Applying Dijkstra's Algorithm5min
Inclusion and Exclusion Constraints1min
Connectivity Analytics3min
Disconnecting a Graph1min
Connectedness: Indegree and Outdegree3min
Community Analytics and Local Properties7min
Global Property: Modularity7min
Centrality Analytics8min
Optional Lecture 1: Bi-directional Dijkstra Algorithm2min
Optional Lecture 2: Goal-directed Dijkstra Algorithm2min
Optional Lecture 3: Power Law Graphs2min
Optional Lecture 4: Measuring Graph Evolution3min
Optional Lecture 5: Eigenvector Centrality6min
Optional Lecture 6: Key Player Problems2min
3 leituras
What to learn in this module10min
If this module takes a little longer... that's OK!10min
Download All Slides for Module 310min
2 exercícios práticos
Graph Analytics Applications34min
Connectivity, Community, and Centrality Analytics38min
4 horas para concluir
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 horas para concluir
10 vídeos (Total 78 mín.), 12 leituras, 2 testes
10 videos
Hands-On: Downloading, Installing, and Running Neo4j5min
Hands-On: Getting Started With Neo4j6min
Hands-On: Modifying a Graph With Neo4j7min
Hands-On: Importing Data Into Neo4j13min
Hands-On: Basic Queries in Neo4j With Cypher - Part 16min
Hands-On: Basic Queries in Neo4j With Cypher - Part 26min
Hands-On: Path Analytics in Neo4j Using Cypher - Part 18min
Hands-On: Path Analytics in Neo4j Using Cypher - Part 211min
Hands-On: Connectivity Analytics in Neo4j With Cypher9min
12 leituras
About the Supplementary Resources10min
Downloading, Installing, and Running Neo4j - Supplementary Resources10min
Getting Started With Neo4j - Supplementary Resources10min
Adding to and Modifying a Graph - Supplementary Resources10min
Download datasets used in this Graph Analytics with Neo4j10min
Importing Data Into Neo4j - Supplementary Resources10min
FAQ10min
Basic Queries in Neo4j With Cypher - Supplementary Resources10min
Path Analytics in Neo4j With Cypher - Supplementary Resources10min
Connectivity Analytics in Neo4j with Cypher - Supplementary Resources10min
Assignment: Practicing Graph Analytics in Neo4j With Cypher10min
Download All Neo4j Supplementary Resources (PDFs)10min
2 exercícios práticos
Quiz: Graph Analytics With Neo4j18min
Assessment Questions on 'Practicing Graph Analytics in Neo4j With Cypher'18min
Avaliações
Principais avaliações do GRAPH ANALYTICS FOR BIG DATA
por KM16 de Dez de 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.
por JT25 de Out de 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.
por JA27 de Out de 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 ....
por LS23 de Mar de 2019
Nice introduction of multiple graph packages, however I missed some more applied cases, covering a real graph problem investigation (particularly how to associate Neo4j with GraphX).
Sobre Programa de cursos integrados Big DataBig Data
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.
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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.
What is the refund policy?
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