Learn Neo4j Database and Graph Algorithms
3.2 (13 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
146 students enrolled

Learn Neo4j Database and Graph Algorithms

Run blazingly fast queries on complex graph datasets with the power of the Neo4j graph database
3.2 (13 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
146 students enrolled
Created by Packt Publishing
Last updated 6/2019
English [Auto-generated]
Current price: $129.99 Original price: $199.99 Discount: 35% off
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This course includes
  • 4.5 hours on-demand video
  • 1 downloadable resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Understand the science of graph theory, databases, and its advantages over traditional databases
  • Install Neo4j and learn the most common practices of traversing data
  • Understand the problems while working with nodes and with large graphs of information
  • Learn proper skills for data modelling and querying capabilities of graph databases
  • Understand why relational databases are replaced by graph databases
  • Learn Cypher Query Language that can be used for modifying, creating, and deleting data
  • Use Neo4j graph algorithms library with your real data
  • Solve routing problems by finding paths inside a connected graph
  • Create a group of nodes sharing common properties, aka communities
  • Build a recommendation system using similarity measurement between nodes
  • No previous graph database experience is required; however, some basic database knowledge will help you understand the concepts more easily.

With increase in complexity of data relationships, graph databases are quickly becoming the de-facto standard for organizations who manage large volumes of connected data. Neo4j is a graph database that allows traversing huge amounts of data with ease. It is the world's leading graph database management system which is designed for optimizing fast management, storage, and traversal of nodes and relationships.

Starting with a brief introduction to graph theory, this course will show you the advantages of using graph databases along with data modelling techniques for graph databases. You will gain practical hands-on experience with commonly used and lesser known features for updating graph store with Neo4j's Cypher query language. You will learn to use it for artificial intelligence, fraud detection, graph-based search, network ops & security, and many other use cases.

Furthermore, you will learn the important graph algorithms which are used in Neo4j’s graph analytics platform wherein you will explore various high-performance graph algorithms that help reveal hidden patterns and structures in your connected data. You will also gain skills to use the algorithms efficiently to understand, model, and predict complicated dynamics.

By the end of this course, you will be confident using graph analytics with Neo4j to effectively handle large volume of connected data and to use its quick insights to wield powerful results.

Meet Your Expert(s):

We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:

  • Shehzad Ahmed is an enthusiast software engineer having a great grip and hands-on experience with multiple programming languages i.e. C/C++ Java and C#.NET, JS, PHP. He has worked on web and mobile development with various APIs and open source libraries. Currently, he is working as a Magento 2 E-commerce developer at fmeextension. Besides that, he is also a freelancer on Fiverr since the last 2 years and has completed over 200 projects with 4.9/5.0 rating and has worked on Neo4j extensively.

  • Estelle Scifo has more than 7 years of work experience as a data scientist. As a Neo4j certified professional, she uses graph databases on a daily basis and takes full advantage of its features to build efficient machine learning models out of this data. Besides that, she is also a data science mentor to guide newcomers into the field. The domain expertise and the beginner’s mind make her an excellent teacher.

Who this course is for:
  • This course is for developers, web developers and aspiring data scientists who are new to graph analytics and who wish to use the power of Neo4j for their data in their applications.
Course content
Expand all 44 lectures 04:29:56
+ Learning Neo4j 3.x
24 lectures 02:10:03

This course gives you an overview of the course.

Preview 03:46

This video will give you a better understanding of basics of Neo4j 3.x.

  • Study the Graph Theory

  • Introduce the Graph Databases

  • Understand the Basics of Neo4j

Basics of Neo4j 3.x

In this video, you will see how to choose the right operating system.

  • Study about the System Requirement Description

System Requirements

This video will solve the problem while downloading the right file for the installation of Neo4j Desktop.

  • Install the Java JDK 8

  • Download the right file for Neo4j Desktop

  • Install the Neo4j Desktop

Setting up Neo4j Desktop

In this video, you will look at Graph Database. You will also see the comparison between Relational Database and Graph Database.

  • Look at Graph Database

  • Compare Relational Database and Graph Database

Preview 06:10

This video will give you a better understanding of nodes. You will be working on single node, multiple nodes, node with a label, node with multiple labels, and adding properties to the nodes.

  • Look at the working of nodes

Creating Nodes in Neo4j

In this video, you will see creating instant relationships on nodes, adding label, and properties to relationships.

  • Create instant relationships on nodes

  • Add labels and properties to relationship

Creating Relationships between Nodes

In this video, you will see the building blocks of Bank Management System. You will also see roles of building blocks.

  • Look at the building blocks of Bank Management System

  • Understand the roles of building blocks

Working with Bank Management System

In this video, you will look at merging the node with label and properties. You will also see merging the relationships. This video will give a brief on OnCreate and OnMerge command.

  • Look at the Merge Command

  • Work with onCreate and onMerge command

Working with Merge Clause

This video will give you a better understanding of set, delete, remove, and foreach clause

  • Look at the different clauses

Working with WRITE Clauses

In this video, you will see match clause, optional-match clause, and where clause.

  • Work with match, optional-match, and where clause

Working with READ Clause

In this video, you will see why query optimization is important? You will also see node label, indexes, and constraint.

  • Look at the important of query optimization

  • Use node label, indexes, and constraints

  • Use size with relationship

Optimizing Clauses and Queries

In this video, you will look at toUPPER function, toLOWER function, substring function, replace, and split function

  • Look at the different functions

Understanding String Functions

This video will give you a better understanding of different mathematical functions.

  • Look at the different mathematical function

Understanding Mathematical Functions

In this video, you will see what is user-defined function, input declaration, and output declaration and write our first user-defined function.

  • Understand user-defined function

  • Learn about input and output declaration

Writing user-defined Functions

In this video you will see what testing is? You will also get a better understanding of integration testing.

  • Look at what testing is?

  • Understand integration testing

Writing Integration Tests for User-defined function

In this video, you will implement different functions of the Bank Management System project

  • Understand the different functions of Bank Management System

Implementing the Functions in Project

In this video, you will look at different features on Home Screen of Neo4j Admin Panel.

  • Look at the different features of Neo4j Admin Panel

Understanding Neo4j Admin Panel

This video will give you a better understanding on how to create a backup of the database and then how to restore it.

  • Create a backup of the database

  • Restore the backup of the database

Working with Database Backup

In this video, you will see useful commands and key shortcuts.

  • Learn useful commands and key shortcuts

Useful Commands and Keyboard Shortcuts

In this video, you will take a look at the different formats of your output and save the graph on your disk.

  • Learn different formats of output

Query and Command Line Tips

In this video, you will see how constraints are added to the project.

  • Add constraint to the project

Adding Constraints to our Project

In this video you will look at next level of Neo4j.

  • Look at the next level of Neo4j

What could be next?

This video will summarize the course.

  • Look at the summarizing of the course

Summarizing the Course
Test Your Knowledge
5 questions
+ Exploring Graph Algorithms with Neo4j
20 lectures 02:19:53

This video will give you an overview about the course.

Preview 03:33

The goal of this video is to understand what the applications of graph algorithms are.

  • Discover graph applications

  • Learn about machine learning applications

  • Understand the intersection between machine learning and graphs

Real-World Examples of Graph Algorithms Applications

The aim of this video is to discover the different kind of graphs and why it matters.

  • Discover what are the different graph properties

  • See applications with examples

  • Understand why graph categories are important in this course

Graph Properties

The goal of this video is to set up your environment.

  • Install Neo4j Desktop

  • Install graph algorithm library

  • Check that the installation was successful

Library Installation

The goal of this video is to present the shortest path algorithm techniques and see it in action in Neo4j.

  • Learn about graph traversal techniques

  • Run the Dijkstra’s algorithm on simple example

  • Apply this algorithm on a simple graph

The Shortest Path Algorithm

The aim of the video is to become familiar with the Neo4j graph algorithm library pipeline.

  • Understand the guiding lines of the library

  • Learn how to define the subgraph to be used

  • Get the result in the most efficient way

More about Graph Algorithms Library Principles

In this video, you will start building the first real-world application of graph algorithm- A path finder for public transport.

  • Load the prepared graph data

  • Find the shortest path between two stations (simple scenario)

  • Understand the algorithm details with more subtle examples

Find Shortest Path Between Two Stations

The goal of this video is to discover what are the other algorithms related to path finding.

  • Learn about other shortest path finder algorithms

  • Discover K-shortest path finder

  • Discover the all-pair shortest path finder

Alternative Algorithms

The aim of this video is to solve the issues encountered by a public transport route planning system.

  • Consider connections in path finding

  • Measure the distance from one station to all others

  • Measure the distance between all stations

Finding Alternative Routes

The aim of the video is to understand what is the meaning of centrality and show a first measurement

  • Define centrality in different contexts

  • Discover a famous dataset for graph analysis

  • Quantify centrality the simple way

Centrality Detection Principles

The goal of this video is to understand how the pagerank algorithm, developed by Google, works

  • Build the pagerank algorithm formula

  • Compare with the previous centrality detection approach

  • Evaluate the impact of the various parameters

The PageRank Algorithm

The goal of this video is to discover other centrality detection methods and compare them

  • Understand why different approaches are needed

  • Test these approaches on a dataset

  • Visualize the differences

A Comparison of Other Centrality Detection Algorithm

The aim of this video is identify the most important people in a company

  • Understand the graph model

  • Choose the proper centrality algorithm

  • Analyze and discuss the results

Influencer Detection

The goal of this video is to give an overview of the various community detection algorithms implemented in Neo4j

  • Learn about the application of community detection

  • Learn about the different algorithms

  • Analyze the result of each algorithm on a simple dataset

Algorithms Strength and Differences

The aim of this video is to summarize the techniques that can be used to build a recommendation system, focusing on those that can work on real-time with Neo4j

  • Learn about some simple recommendation engine techniques

  • Discover the Northwind dataset

  • Write queries for recommendation without graph algorithms

Building a Real-Time Recommendation Engine

The goal of this video is to show how community detection can be used in the context of recommendation

  • Apply community detection algorithm to group similar products

  • Use this information in a recommendation system

  • Learn how to choose the best performing recommendation method

Community-Based Recommendations

The goal of this video is to learn how similarity measurement can help recommendations

  • Discover how to quantify similarity between nodes

  • Measure this similarity on the Northwind dataset products

  • Wrap up the recommendation method we have used

Using Similarity Measures

The aim of this video is to discover the link prediction algorithms, especially those available in Neo4j

  • Understand what is link prediction and why it is important

  • Discover link prediction algorithm

  • Use the functions implemented in Neo4j

Link Prediction in Neo4j

The goal of this video is to understand how machine learning techniques can be applied on graphs

  • Define the problem as a machine learning problem

  • Learn how to add graph features in your model

  • Learn about automatic feature extraction with graph embedding

Machine Learning on Graphs

The goal of this video is to summarize what we have learned in this course and show perspectives about the future of graphs and machine learning

  • Summarize the key points of the course

  • Get some advices about future learning

  • Discover a new visualization tool helpful for graph analysis

Conclusions and Perspectives
Test Your Knowledge
5 questions