Learn Neo4j Database and Graph Algorithms

Graph databases are rapidly becoming the preferred solution for organizations dealing with increasingly complex data relationships. This course dives into the world of graph databases, focusing on Neo4j, the leading graph database management system. Learn how to efficiently manage, store, and traverse vast amounts of interconnected data with ease.

We'll begin with a foundational introduction to graph theory and explore the significant advantages of using graph databases over traditional approaches. You'll master essential data modeling techniques for graph databases, enabling you to structure your data for optimal performance.

Gain practical, hands-on experience with Neo4j's Cypher query language, a powerful tool for updating your graph store. Discover how to leverage Neo4j for a wide range of applications, including:

• Artificial Intelligence (AI)
• Fraud Detection
• Graph-Based Search
• Network Operations & Security
• And many other innovative use cases.

This course delves into crucial graph algorithms utilized within Neo4j’s graph analytics platform. Explore high-performance algorithms designed to uncover hidden patterns and structures within your connected data. You'll develop the skills to apply these algorithms effectively to understand, model, and predict complex dynamics.

By the course's conclusion, you'll possess the confidence to utilize graph analytics with Neo4j to handle large volumes of connected data and extract actionable insights for powerful results.

Meet Your Expert(s):

• Shehzad Ahmed: A seasoned software engineer with extensive experience in multiple programming languages (C/C++, Java, C#, .NET, JS, PHP) and a strong background in web and mobile development. Currently a Magento 2 E-commerce developer at fmeextension and a highly-rated freelancer on Fiverr with over 200 projects completed, including significant work with Neo4j.
• Estelle Scifo: A data scientist with over 7 years of experience and a Neo4j certified professional. Estelle leverages graph databases daily to build efficient machine learning models. She also serves as a data science mentor, bringing a beginner-friendly approach to teaching and a deep understanding of the field.