Course Description
Take this course introduction to graph database and analytics and how Neo4j is used in many enterprises to implement key use cases. You’ll learn about the differences between a relational data model and a graph property model. Then, you’ll learn about the components of the Neo4j Graph Database & Analytics platform and how to set up your development environment for learning Cypher, the Neo4j query language. You’ll learn to write Cypher queries to retrieve data from the Neo4j database and how to write Cypher statements to create, update, and delete data in the Neo4j database. You will learn how to add constraints and indexes to a Neo4j database, how to monitor queries, and how to import relational CSV data into a Neo4j database. You will be able to run Data Science algorithms directly on top of the Graph Database and you will be able to train ML models in a few lines of Python code.
Course Modules:
- Introduction to Graph Databases
- Introduction to Neo4j
- Use Cases for Graph Databases
- Setting Up Your Development Environment
- Introduction to Cypher
- Getting More Out of Queries
- Graph Databases and visualization
- Graph Data Science
- Machine Learning on Graphs
- Describe what a graph database is and the graph property model
- Describe the features and components of Neo4j Graph Database & Analytics
- Set up your development environment with Neo4j Desktop or a Neo4j Sandbox
- Write basic Cypher queries to retrieve nodes and relationships
- Write advanced Cypher queries where you control the query processing and how results are returned
- Write Cypher statements to create, update, and delete nodes, relationships, and properties
- Write Cypher statements to:
- Analyze and monitor queries
- Create constraints and indexes
- Import CSV data into the Neo4j database
- Setup a data science environment on your Graph Database
- Run centrality, community, ranking and paths algorithms on any projection of your data
- Train a model and apply Machine Learning classification and regression pipelines.
You will need your own laptop and the latest version of Neo4j Desktop downloaded on this laptop prior to the start of class or make sure you have access to Neo4j Sandbox and Google Colab.
Xavier Pilas is Sales Engineer at Neo4j based in Singapore. He is French, having left France in 2005 he lived and worked all over the world, in Dublin, Salt Lake City and Singapore. He worked mostly in Finance institutions (broker, investment banks) as a software developer and was involved in front-to-back software development in areas like Trading, Futures and Options clearing, Margins or Reconciliations. He started his career coding in Java, Python, Turbo Pascal and later worked on C & C++.
He is a Pre Sales consultant for five years and enjoys discussing use cases with prospects and clients to solve business challenges with graph databases. As an engineer, he loves to work on real-life use cases and leverage the power of graphs for fraud detection, recommendations, network topology, etc.
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