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Training Information

Join us on June 6 for hands on experience with Neo4j software. When registering, you will be able to add on the cost of trainings. Please read the descriptions of each to learn of any pre-requisite for the courses. Those who participate in the training will select either (1) 7 hour training or (2) 3.5 hour trainings, one in the morning and one in the afternoon. Further information on how to select a training course(s) will be provided to registrants, who have opted to add on training, in the coming months. We are working to add more trainings and will release a full schedule soon.

June 6 at GraphConnect

Training Course Descriptions

Basic Cypher Querying

Duration: 4 hours

Skill Level: Beginner

Prerequisite Course: Graphs & Graph Databases

Course Description: This course is the starting point for learning practical skills with Cypher. The central focuses are basic Cypher syntax, plus the most common tools and commands for issuing queries to a Neo4j graph database.

Basic Cypher Querying is a required prerequisite for anyone who needs to write, interpret, or debug Cypher strings. Additionally, it is strongly recommended for everyone who will work with Neo4j in any capacity, because a practical understanding of querying is an invaluable tool for understanding graphs in general.

Course Modules:

  • 1. Cypher Syntax, MATCH, and RETURN
  • 2. WHERE
  • 3. Working with Patterns
  • 4. Using Indexes

At the completion of this course, you should be able to:

  • ● Use correct Cypher syntax for nodes, labels, properties, and relationships
  • ● Use MATCH, RETURN, and WHERE clauses to execute simple queries
  • ● Create and use Property Indexes as needed


Neo4j Graph Data Science - Getting started

Skill Level: Beginner

Prerequisites: None - But you are most likely a practitioner that works with data

Course Description: This course is intended to demystify Graph Data Science by covering the fundamentals of graph theory and graph algorithms through easy to follow examples and exercises.

Course Modules:

  • 1. Graphs in theory vs in practice
  • 2. Graph algorithms
  • 3. Unsupervised vs supervised learning
  • 4. From data to wisdom
  • 5. The Neo4j Graph Data Science Platform

At the completion of this course, you should be able to:

  • ● Identify when graph data science can help
  • ● Have knowledge about how to get started with Neo4j Graph Data Science platform
  • ● Un-supervised learning with graph algorithms


Basic Neo4j Administration

Duration: 8 hours

Skill Level: Intermediate

Prerequisite Courses: Graphs & Graph Databases, Basic Cypher Querying, Data Management with Cypher

Course Description: This course introduces you to the common administration tasks for managing Neo4j Enterprise Edition, either in a development environment or in a production environment. First, you learn about what Neo4j is. Next you learn about the various architectures where Neo4j is used and you learn about the versions and editions of Neo4j where you install Neo4j Enterprise Edition.

Then you learn the basics of managing a Neo4j instance and how to perform both offline and online backups as well as using the cypher-shell utility for accessing the database from a terminal. You will also learn how to manage plugins to be used by the Neo4j instance and how to load a database using the import tool.

In this course, you will learn by performing 12 hands-on exercises using a Docker Neo4j instance.

Course Modules:

  • 1. Introduction to Neo4j
  • 2. Overview of Neo4j Administration
  • 3. Managing a Neo4j Instance
  • 4. Using cypher-shell to Manage Databases
  • 5. Copying Databases
  • 6. Changing the Database Location
  • 7. Checking Database Consistency
  • 8. Scripting to Manage Databases
  • 9. Configuring Plugins
  • 10. Changing the HTTP Port
  • 11. Importing Data

At the completion of this course, you should be able to:

  • ● Determine which deployment option to use
  • ● Start a Neo4j instance
  • ● Stop the Neo4j instance
  • ● Set the password for the neo4j user
  • ● Copy a Neo4j database
  • ● Modify the location for a Neo4j database
  • ● Check the consistency of a Neo4j database
  • ● Create scripts for modifying a Neo4j database
  • ● Manage plugins for a Neo4j database
  • ● Configure the HTTP port used by the Neo4j instance/li>
  • ● Perform an online backup of a Neo4j database
  • ● Create a database with the import tool


Building a Neo4j Application with Node.js

Duration: 3.5 hours

Skill Level: Beginner/intermediate

Prerequisites: Working knowledge of JavaScript, NPM and the Node.js ecosystem. We also assume that you have at least a basic knowledge of Neo4j.

Course Description: In this course, we walk through the steps to integrate Neo4j into an existing Node.js project. We will follow the steps to create an instance of the Neo4j JavaScript Driver, learn how to use sessions and transactions, and use that knowledge to replace hardcoded API responses with data from a Neo4j Sandbox instance.



Cypher Query Tuning

Duration: 8 hours

Skill Level: Advanced

Prerequisite Courses: Graphs & Graph Databases, Basic Cypher Querying, Intermediate Cypher Querying, Data Management with Cypher, Graph Data Modeling

Course Description: This course dives deep into the inner workings of Cypher, in order to discuss strategies for optimizing query performance. This includes an exploration of Cypher query planning, and how the physical data structures affect the cost of information access.

This course makes reference to, but does NOT deeply explore, the effect of data modeling choices on query cost. That discussion is covered in the courses Graph Data Modeling and Implementing Graph Models. Instead, this course focuses on how to get best query results from an invariant model.

Note that this course is twice as long as most, at 8 hours. It is usually delivered in two parts for easier consumption.

Course Modules:

  • 1. Preparing for Query Tuning
  • 2. How queries work in Neo4j
  • 3. Controlling Row Cardinality
  • 4. Neo4j Behind the Scenes
  • 5. Optimizing Property Access
  • 6. Node Degree Shortcuts
  • 7. Monitoring Running Queries

At the completion of this course, you should be able to:

  • ● Define the terms row and DB hit in the context of Cypher querying
  • ● Use EXPLAIN and PROFILE to identify weaknesses in a query plan
  • ● Use Cypher tools to minimize the number of rows processed in a query
  • ● Use best practices for minimizing property access
  • ● Use monitoring tools to identify the underlying causes of a long-running query
Data Management with Cypher

Duration: 4 hours

Skill Level: Beginner

Prerequisite Courses: Graphs & Graph Databases, Basic Cypher Querying

Course Description: This course introduces the tools used for manipulating Neo4j graph data using Cypher. This includes creating, modifying, and deleting nodes, relationships, labels, and properties. In addition, this course shows how the schemaless nature of Neo4j can be both useful and dangerous.

Strategies for data governance and safety are discussed in Data Management: Import and Governance, for which this course is a prerequisite.

Course Modules:

  • 1. Creating Nodes
  • 2. Creating Relationships
  • 3. Deleting Nodes and Relationships
  • 4. Merging Data in the Graph

At the completion of this course, you should be able to:

  • ● Write Cypher statements to create and delete nodes and relationships
  • ● Write Cypher statements to create, modify, and remove labels and properties
  • ● Identify the difference between CREATE and MERGE, including use cases for each


Data Management: Import & Governance

Duration: 4 hours

Skill Level: Intermediate

Prerequisite Courses: Graphs & Graph Databases, Basic Cypher Querying, Data Management with Cypher

Course Description: This course explores four ways to import bulk data into Neo4j. In addition, it discusses some tools and strategies for doing so “safely”, with respect to duplication, data typing, and cleanliness. This is an extension of the conversation begun in the course Data Management with Cypher.

Course Modules:

  • 1. Defining Constraints
  • 2. Overview of Data Import
  • 3. LOAD CSV
  • 4. Loading with APOC
  • 5. neo4j -admin import
  • 6. Neo4j ETL

At the completion of this course, you should be able to:

  • ● Create and manage constraints
  • ● Import data into Neo4j using four methods: LOAD CSV, APOC, neo4j-import, and the Neo4j ETL tool
  • ● During the import process, use Cypher tools to manage data types and formatting


Graph Data Modeling

Duration: 4 hours

Skill Level: Beginner

Prerequisite Course: Graphs & Graph Databases

Course Description: This course explores the philosophy and process behind creating graph models. It examines how the data structures and uses of a graph inform modeling decisions, and how these differ from the usual circumstances and decisions involved in designing a relational model.

Note that the exercises in this course do not use the Neo4j platform. Instead, we use the Arrows whiteboarding app to work entirely on conceptual modeling problems. The tools and strategies for implementing a model in Neo4j are covered in the class Implementing Graph Models.

Course Modules:

  • 1. Introduction to Graph Data Modeling
  • 2. Designing the Initial Graph Data Model
  • 3. Graph Data Modeling Core Principles
  • 4. Common Graph Structures
  • 5. Refactoring and Evolving a Model

At the completion of this course, you should be able to:

  • ● Describe the seven steps involved in the initial graph modeling process
  • ● Define the terms intermediate node and linked list
  • ● Design a graph model from scratch using Neo4j best practices


Graphs & Graph Databases

Duration: 4 hours

Skill Level: Beginner

Course Description: This course is intended to set the stage for future technical study of Neo4j. It begins by examining the context in which Graph Databases exist, including an overview of the historical evolution of database technologies and comparative analysis of Graph Databases vs. the ubiquitous Relational Database.

In addition, this course begins exploring the Neo4j platform by introducing the data structures, query language, and basic system architecture.

Graphs & Graph Databases is a prerequisite for every other Neo4j University course.

Course Modules:

  • 1. Persistence Strategies
  • 2. Relational vs Index-Free Adjacency
  • 3. Introduction to Property Graphs
  • 4. Introduction to Cypher
  • 5. The Neo4j Graph Platform

At the completion of this course, you should be able to:

  • ● Identify the relative strengths and weaknesses of different database types
  • ● Define the term Index-Free Adjacency, and explain how it enables fast traversal of long paths
  • ● Define the terms node, relationship, label, and property
  • ● Define and distinguish the components of the Neo4j Platform
  • ● Create and populate a graph using Neo4j Desktop and Neo4j Browser


Implementing Graph Models

Duration: 4 hours

Skill Level: Advanced

Prerequisite Courses: Graphs & Graph Databases, Basic Cypher Querying, Data Management with Cypher, Data Management: Import & Governance, Graph Data Modeling

Course Description: This module discusses how to implement a graph in Neo4j, using an already-designed data model from an existing data model using Neo4j Best practices. It is heavily hands-on focused, and draws deeply on skills learned in the Data Management courses.

A central theme of this course is learning how to modify the entire graph as the data model requirements change.

Course Modules:

  • 1. Implementing your first model
  • 2. Importing data
  • 3. Profiling queries
  • 4. Refactoring graphsC

At the completion of this course, you should be able to:

  • ● Write Cypher code to populate a database with sample data for the starting data model
  • ● Use Cypher to import data into the graph for a given data model
  • ● Analyze query execution
  • ● Refactor a graph by adding intermediate nodes
  • ● Refactor a graph by adding relationships
  • ● Perform a refactoring on a large database


Intermediate Cypher Querying

Duration: 4 hours

Skill Level: Intermediate

Prerequisite Courses: Graphs & Graph Databases, Basic Cypher Querying

Course Description: This course extends the discussion begun in the Basic Cypher Querying course. It explores a set of Cypher tools that are commonly used in production, but that go beyond what an unsophisticated end user would need to know. This includes subqueries, intermediate results processing, controlling returned results, and an introduction to evaluating query plans with EXPLAIN and PROFILE

Course Modules:

  • 1. Aggregation, Lists, & Dates
  • 2. WITH & Subqueries
  • 3. DISTINCT, ORDER BY, LIMIT
  • 4. Query Best Practices

At the completion of this course, you should be able to:

  • ● Aggregate sets of patterns into lists and integers
  • ● Subdivide complex transactions into simple executable elements using WITH and subqueries
  • ● Closely control the number and order of results
  • ● Use EXPLAIN, PROFILE, and query monitoring tools to evaluate the quality and health of queries
  • ● Genericize query strings using Parameters


Neo4j and Vertex AI Hands on Labs

Duration: 4 hours

Skill Level: Beginner

Prerequisite Courses: You'll need a laptop with a web browser and a Google Cloud Platform (GCP) account. If you don't already have a GCP account, we'll cover how to sign up for one in the lab. No prior knowledge of Neo4j, GCP or Vertex AI is required.

Abstract: Neo4j is the leading graph database vendor. We’ve worked closely with GCP Engineering for years. Our products, AuraDB and AuraDS are offered as managed services on GCP. Neo4j Enterprise Edition, which includes Graph Database, Graph Data Science and Bloom is offered in the Google Cloud Marketplace. In this hands on lab, you’ll get to learn about Neo4j and GCP Vertex AI. The lab is intended for data scientists and data engineers. We’ll walk through deploying Neo4j and Vertex AI on GCP in your own GCP account. Then we’ll get hands on with a real world dataset, building a machine learning pipeline that takes advantage of features generated using Neo4j Graph Data Science to improve prediction in GCP Vertex AI. You’ll come out of this lab with enough knowledge to apply graph feature engineering to your own datasets.

We’re going to analyze the quarterly filings of asset managers with $100m+ assets under management (AUM). These are regulatory filing made to the Securities and Exchange Commission’s (SEC) EDGAR system. We’re going to show how to load that data from a GCP Cloud Storage bucket into Neo4j. We’ll then explore the relationships of different asset managers and their holdings using the Neo4j Browser and Neo4j’s Cypher query language. Finally, we’ll use Neo4j Graph Data Science to create a graph embedding from our data, export that out, and run supervised learning algorithms in GCP Vertex AI. We’ll try to predict what holdings asset managers will maintain or enlarge in the next quarter. If you’re in the capital markets space, we think you’ll be interested in potential applications of this approach to creating new features for algorithmic trading, understanding tail risk, securities master data management and so on. If you’re not in the capital markets space, this session will still be useful to learn about building machine learning pipelines with Neo4j and GCP Vertex AI.