Neo4j Certified Professional Exam Prep

Topic 1 Neo4j Fundamentals

• Basic graph theory and the elements that make a graph
• Graph structures
• Common graph database use cases
• Elements of a Neo4j graph database
• How Neo4j implements index-free-adjacency
• The Movie graph’s data model and data

Topic 2 Cypher Fundamentals

• Reading Data from Neo4j
• Introduction to Cypher
• Retrieving Nodes
• Finding Relationships
• Traversing Relationships
• Filtering Queries
• Writing Data to Neo4j
• Creating Nodes
• Creating a Node
• Creating Relationships
• Updating Properties
• Adding Properties to a Movie
• Merge Processing
• Deleting Data

Topic 3 Importing CSV Data into Neo4j

• Preparing for importing data
• Using the Neo4j Data Importer
• Post-processing for imported data
• Using Cypher to import data

Topic 4 Graph Data Modeling Fundamentals

• What is a graph data model?
• Modeling nodes and creating nodes for an instance model.
• Modeling relationships and creating relationships for an instance model.
• Testing the graph data model.
• Why refactor a graph data model and how labels help.
• Eliminating duplicate data in the graph.
• Using specific relationship types.
• Adding intermediate nodes.

Topic 5 Intermediate Cypher Queries

• Filtering queries
• Controlling results returned
• Working with Cypher data
• Graph traversal
• Pipelining queries
• Subqueries
• Using parameters

Topic 6 Neo4j Graph Data Science

• Basics for how Neo4j GDS works to enable analytics
• How to install GDS and the different licensing options
• Graph projection patterns

Topic 7 Neo4j Applications with Python

• The lifecycle of the Neo4j Driver and how it relates to your application
• How to install and instantiate the Neo4j Python Driver to your Python project
• How read and write transactions work with Neo4j
• Best practices on how to use Neo4j within your Python project.

Final Assessment

• Written Assessment (SAQ)
• Practical Performance (PP)

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

• Able to operate using computer functions
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

• Positive Learning Attitude
• Enthusiastic Learner

Experience

• Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

TBD

Hardware: Window or Mac Laptops

• Database Administrator (specializing in graph databases)
• Data Scientist (working with graph data)
• Neo4j Developer
• Graph Database Consultant
• Data Engineer (focusing on graph technologies)
• Data Architect (implementing graph solutions)
• Backend Developer (integrating graph databases)
• Graph Data Analyst
• Machine Learning Engineer (using graph-based algorithms)
• Data Integration Specialist (for graph databases)
• Recommendation System Developer
• Research Scientist (working on graph theory)
• Social Network Analyst
• Fraud Detection Specialist (using graph patterns)
• Bioinformatics Researcher (using graph databases).

Teh Siew Yee: Teh Siew Yee is a seasoned leader in data science and digital transformation, with over 20 years of experience driving organisational strategy, talent development, and the design of data ecosystems across Asia Pacific and global markets. He has successfully led cross-geographical teams and collaborated with industry leaders from the US, UK, China, India, Japan, South Korea, Australia, and beyond, focusing on leveraging data to achieve business objectives and optimize operations.

With expertise spanning predictive modeling, machine learning, deep learning, and IoT, he has hands-on experience in data architecture, engineering, and analytics. He has also developed comprehensive training programs, equipping all levels of an organisation— from C-suite to working-level employees— with the skills needed for digital transformation. His industry experience covers sectors such as tech, education, finance, aerospace, and eCommerce, making him a sought-after expert in data-driven business strategy.

Quah Chee Yong: Quah Chee Yong is a ACTA trainer. Chee Yong is an experienced professional who has held various Technical, Operations and Commercial positions across several industries A firm believer that AI can create a better world, he has equipped himself with the Knowledge and Skills in the fields of Data Science, Machine Learning, Deep Learning and Cloud Deployment He has a deep passion for training & facilitating and is currently a Singapore WSQ certified Adult Educator. He particularly enjoys the interactive engagements with his fellow trainers and learners.