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Amarnath Gupta
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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/f9xjpp/graph
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What's inside
Syllabus
Welcome to Graph Analytics
Meet your instructor, Amarnath Gupta and learn about the course objectives.
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!
Read more
Syllabus
Welcome to Graph Analytics
Meet your instructor, Amarnath Gupta and learn about the course objectives.
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!
Read more
Graph Analytics
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.
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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
- Introduces key concepts and techniques in graph analytics, which is becoming increasingly important in various industries
- Led by experienced instructor Amarnath Gupta, who is well-regarded for their expertise in graph analytics
- Provides practical examples and hands-on exercises using the popular graph database Neo4j, enhancing the applicability of the concepts learned
- Incorporates industry-standard programming models and frameworks, such as GraphX and Giraph, for building scalable graph analytics applications
- Lacks up-to-date information on the latest advancements and trends in graph analytics
- May require students to have some prior experience with graph theory and data structures to fully benefit from the course
Save this course
Save Graph Analytics for Big Data to your list so you can find it easily later:
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Reviews summary
Big data graph analytics overview
According to students, this course offers a broad and basic introduction to graph analytics for big data. They say that the instructor is knowledgeable and provides clear explanations. However, learners have mixed reactions about the pace of the course and the inclusion of demonstrations over explanations.
Knowledgeable instructor.
"The teacher and explanations is very good."
Clear explanations of concepts.
"The teacher and explanations is very good."
Outdated course material.
"It also seems that some of the course material is not up to date with the current versions of the apps as well."
Lack of depth in explanations.
"We are presenting but not really conveying anything meaningful given the pace that they are covered."
Fast paced.
"My personal opinion but we seem to be just breezing through at a very fast pace the details associated with the applications."
Basic overview of graph analytics.
"An introduction to graph theory, at best."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Graph Analytics for Big Data with these
activities:
Graph Databases: Concepts and Applications
Show steps
Gain a foundational understanding of graph databases and their applications by reading and comprehending this book.
Show steps
-
Read the book
-
Take notes and highlight important concepts
-
Complete the exercises and assignments in the book
Graph Analytics Resources Collection
Show steps
Expand your understanding of graph analytics by compiling a list of relevant resources, including articles, tutorials, and tools.
Browse courses on
Graph Analytics
Show steps
-
Search for online resources related to graph analytics
-
Evaluate the resources and select those that are most relevant and informative
-
Organize the resources into a curated collection
Graph Analytics with NetworkX Tutorial
Show steps
Enhance your practical skills in graph analytics by following a guided tutorial on using the NetworkX library.
Browse courses on
Graph Analytics
Show steps
-
Install NetworkX
-
Follow the tutorial to learn how to create and manipulate graphs
-
Experiment with different graph algorithms and techniques
Five other activities
Expand to see all activities and additional details
Show all eight activities
Identify Graph Patterns Practice
Show steps
Develop your ability to recognize and identify patterns in graphs by engaging in targeted practice drills.
Show steps
-
Find online resources or create your own graph pattern exercises
-
Practice identifying different types of graph patterns
-
Test your skills by completing practice quizzes or challenges
Drill Neo4j Queries
Show steps
Help yourself solidify your understanding of Neo4j queries by practicing and experimenting with writing different queries.
Browse courses on
Neo4j
Show steps
-
Create a sample graph in Neo4j
-
Practice writing Cypher queries to retrieve nodes and relationships from the graph
-
Experiment with different query operators and functions
Graph Analysis Discussion Group
Show steps
Engage with peers to discuss and share knowledge about graph analysis techniques and best practices.
Show steps
-
Join or create a discussion group focused on graph analysis
-
Participate in discussions, ask questions, and share insights
-
Collaborate with others on graph analysis projects
Design a Graph Model for a Real-World Problem
Show steps
Enhance your problem-solving skills by designing a graph model to represent a real-world problem, demonstrate how to store and retrieve data using the model.
Show steps
-
Identify a real-world problem that can be represented as a graph
-
Design a graph schema to represent the entities and relationships in the problem
-
Implement the graph model using a graph database
-
Store and query data using the graph model
-
Evaluate the performance and scalability of the graph model
Contribute to an Open-Source Graph Analytics Project
Show steps
Enhance your practical skills and contribute to the community by actively participating in an open-source project in the field of graph analytics.
Browse courses on
Open Source
Show steps
-
Identify an open-source graph analytics project that aligns with your interests
-
Review the project's documentation and codebase
-
Identify an area where you can contribute
-
Make contributions to the project, such as bug fixes, feature enhancements, or documentation improvements
-
Collaborate with other contributors and maintainers
Graph Databases: Concepts and Applications
Show steps
Gain a foundational understanding of graph databases and their applications by reading and comprehending this book.
Show steps
Show steps
Show steps
- Read the book
- Take notes and highlight important concepts
- Complete the exercises and assignments in the book
Graph Analytics Resources Collection
Show steps
Expand your understanding of graph analytics by compiling a list of relevant resources, including articles, tutorials, and tools.
Browse courses on
Graph Analytics
Show steps
Show steps
Show steps
- Search for online resources related to graph analytics
- Evaluate the resources and select those that are most relevant and informative
- Organize the resources into a curated collection
Graph Analytics with NetworkX Tutorial
Show steps
Enhance your practical skills in graph analytics by following a guided tutorial on using the NetworkX library.
Browse courses on
Graph Analytics
Show steps
Show steps
Show steps
- Install NetworkX
- Follow the tutorial to learn how to create and manipulate graphs
- Experiment with different graph algorithms and techniques
Five other activities
Expand to see all activities and additional details
Show all eight activities
Identify Graph Patterns Practice
Show steps
Develop your ability to recognize and identify patterns in graphs by engaging in targeted practice drills.
Show steps
Show steps
Show steps
- Find online resources or create your own graph pattern exercises
- Practice identifying different types of graph patterns
- Test your skills by completing practice quizzes or challenges
Drill Neo4j Queries
Show steps
Help yourself solidify your understanding of Neo4j queries by practicing and experimenting with writing different queries.
Browse courses on
Neo4j
Show steps
Show steps
Show steps
- Create a sample graph in Neo4j
- Practice writing Cypher queries to retrieve nodes and relationships from the graph
- Experiment with different query operators and functions
Graph Analysis Discussion Group
Show steps
Engage with peers to discuss and share knowledge about graph analysis techniques and best practices.
Show steps
Show steps
Show steps
- Join or create a discussion group focused on graph analysis
- Participate in discussions, ask questions, and share insights
- Collaborate with others on graph analysis projects
Design a Graph Model for a Real-World Problem
Show steps
Enhance your problem-solving skills by designing a graph model to represent a real-world problem, demonstrate how to store and retrieve data using the model.
Show steps
Show steps
Show steps
- Identify a real-world problem that can be represented as a graph
- Design a graph schema to represent the entities and relationships in the problem
- Implement the graph model using a graph database
- Store and query data using the graph model
- Evaluate the performance and scalability of the graph model
Contribute to an Open-Source Graph Analytics Project
Show steps
Enhance your practical skills and contribute to the community by actively participating in an open-source project in the field of graph analytics.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify an open-source graph analytics project that aligns with your interests
- Review the project's documentation and codebase
- Identify an area where you can contribute
- Make contributions to the project, such as bug fixes, feature enhancements, or documentation improvements
- Collaborate with other contributors and maintainers
Career center
Learners who complete Graph Analytics for Big Data will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use their knowledge of data analysis tools and techniques to extract meaningful insights from data. They may work with structured or unstructured data, and they may use a variety of statistical and machine learning techniques to identify trends and patterns. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Data Analyst. This course will teach you how to model data into a graph database, perform analytical tasks over the graph in a scalable manner, and apply these techniques to understand the significance of your data sets for your own projects.
Data Scientist
Data Scientist
Data Scientists use their knowledge of data science techniques to solve business problems. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Data Scientist. This course will teach you how to apply graph analytics techniques to identify patterns and trends in data, which can help you solve business problems more effectively.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use their knowledge of machine learning techniques to develop and deploy machine learning models. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Machine Learning Engineer. This course will teach you how to use graph analytics techniques to identify patterns and trends in data, which can help you develop more accurate and effective machine learning models.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They may work with a variety of programming languages and technologies. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Software Engineer. This course will teach you how to use graph analytics techniques to design and develop more efficient and scalable software applications.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases. They may work with a variety of database management systems. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Database Administrator. This course will teach you how to use graph analytics techniques to design and implement more efficient and scalable databases.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and data analysis techniques to identify and solve business problems. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Business Analyst. This course will teach you how to use graph analytics techniques to identify patterns and trends in data, which can help you solve business problems more effectively.
Data Architect
Data Architect
Data Architects design and implement data management solutions. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Data Architect. This course will teach you how to use graph analytics techniques to design and implement more efficient and scalable data management solutions.
Information Architect
Information Architect
Information Architects design and implement information systems. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Information Architect. This course will teach you how to use graph analytics techniques to design and implement more efficient and scalable information systems.
Knowledge Engineer
Knowledge Engineer
Knowledge Engineers design and implement knowledge management systems. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Knowledge Engineer. This course will teach you how to use graph analytics techniques to design and implement more efficient and scalable knowledge management systems.
Ontologist
Ontologist
Ontologists develop and maintain ontologies. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Ontologist. This course will teach you how to use graph analytics techniques to design and implement more efficient and scalable ontologies.
Taxonomist
Taxonomist
Taxonomists develop and maintain taxonomies. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Taxonomist. This course will teach you how to use graph analytics techniques to design and implement more efficient and scalable taxonomies.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies and procedures. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Data Governance Analyst. This course will teach you how to use graph analytics techniques to design and implement more efficient and scalable data governance policies and procedures.
Metadata Manager
Metadata Manager
Metadata Managers develop and maintain metadata repositories. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course can help you develop the skills you need to be a successful Metadata Manager. This course will teach you how to use graph analytics techniques to design and implement more efficient and scalable metadata repositories.
Librarian
Librarian
Librarians organize and manage information resources. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course may be useful for you if you are interested in becoming a Librarian. This course will teach you how to use graph analytics techniques to organize and manage information resources more efficiently and effectively.
Archivist
Archivist
Archivists preserve and manage historical records. They may work with a variety of data sources, including structured and unstructured data. The Graph Analytics for Big Data course may be useful for you if you are interested in becoming an Archivist. This course will teach you how to use graph analytics techniques to preserve and manage historical records more efficiently and effectively.
For more career information including salaries, visit:
OpenCourser.com/course/f9xjpp/graph
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Graph Analytics for Big Data.
Save
Offers a deep dive into graph databases, providing theoretical grounding and practical advice. Useful for gaining a broader understanding of the theory and applications of graph databases.
Explores the fundamentals of graph analytics, focusing on practical applications and case studies. Offers foundational knowledge for understanding the concepts and techniques covered in the course.
Offers a deep dive into graph-based semi-supervised learning methods. Useful for understanding the advanced techniques used in graph analytics for data classification and prediction.
Save
Offers a comprehensive overview of data mining concepts and techniques. Provides a foundation for understanding the data mining techniques used in graph analytics.
Provides a comprehensive overview of network analysis methods and their applications in various fields. Serves as a reference guide for understanding the theoretical underpinnings and methodologies used in graph analytics.
Provides a comprehensive overview of information visualization techniques and principles. Useful for understanding the visualization techniques used in graph analytics to represent and interpret data.
Offers a comprehensive introduction to machine learning, including supervised and unsupervised learning techniques. Provides foundational knowledge for understanding the machine learning algorithms used in graph analytics.
Provides a foundational understanding of graph theory concepts and algorithms. Useful for gaining a deeper understanding of the mathematical underpinnings of graph analytics.
Provides a general overview of data science concepts and techniques, including data mining. Offers insights into the broader context of data analytics and its applications in various business domains.
Save
Provides a comprehensive overview of deep learning techniques and architectures. Useful for understanding the potential applications of deep learning in graph analytics.
Offers a comprehensive guide to Hadoop, a widely used framework for big data processing. Provides background on the Hadoop ecosystem and its applicability to graph analytics.
Offers a practical guide to natural language processing (NLP) techniques using Python. Can be useful for understanding the NLP techniques used in graph analytics for text data.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/f9xjpp/graph
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Effort
4 Weeks, 3-5 hours/week
Via
Coursera
Institution
University of California San Diego
Instructor
Amarnath Gupta
Language
English
Transcripts
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آذربایجان دیلی
This course belongs to a
collection
called
Big Data. It's comprised of seven courses:
Good to know
- Introduces key concepts and techniques in graph analytics, which is becoming increasingly important in various industries
- Led by experienced instructor Amarnath Gupta, who is well-regarded for their expertise in graph analytics
- Provides practical examples and hands-on exercises using the popular graph database Neo4j, enhancing the applicability of the concepts learned
- Incorporates industry-standard programming models and frameworks, such as GraphX and Giraph, for building scalable graph analytics applications
- Lacks up-to-date information on the latest advancements and trends in graph analytics
- May require students to have some prior experience with graph theory and data structures to fully benefit from the course
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