Introduction to Graph Databases using Neo4J
Learn the fundamentals of graph databases and build a recommendation engine using Neo4J. Ideal for beginner developers, this course offers step-by-step guidance and visual training to accelerate learning. Gain the skills to solve real-world problems with collaborative filtering.
What you’ll learn
- Fundamentals of graph database
- Data modeling
- CRUD operations and Aggregation
- Building recommendations using graph database
Graph databases are gaining popularity these days because of their ease of use, simplicity, and agility. As compared to relational or document databases, graph databases are great at expressing real-world data models with same set of semantics as a product manager would express. Unlike document databases, it supports transactional operations. Unlike relational databases, it supports fast querying across large databases.
eBay is successfully using Neo4J graph databases for optimizing routes for local delivery. Walmart is using the Neo4J database for real-time local recommendations. Graph databases are also popular for fraud detection use cases.
In this course, you will learn the fundamentals of graph databases. No prior background in a graph database is assumed, which makes it ideal for beginner developers. I’ll cover the rationale behind using a graph database.
Content and Overview
This course teaches you how to build a graph database using Neo4J. You will work along with me step by step to build the following answers
Introduction to Graph databases
Introduction to Neo4j
Build real-world recommendations using Neo4j
What am I going to get from this course?
Learn to build a recommendation engine from a professional trainer from your desk.
Over 10 lectures teaching you how to build a recommendation engine using a graph database
Suitable for beginner programmers and ideal for users who learn faster when shown.
Visual training method, offering users increased retention and accelerated learning.
Breaks even the most complex applications down into simplistic steps.
Offers challenges to students to enable the reinforcement of concepts. Also, solutions are described to validate the challenges.
At the end of the course you’ll be able to demonstrate your command of graph databases and will be ready to build brand-new applications. A graph database is also useful for solving Graph Neural network challenges.
Who this course is for:
- Beginner developer who are curious to learn about how to apply collaborative filtering to solve real world problems.
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