Overview
Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Learn how to build a movie recommendation system using knowledge graphs and discover why major tech companies like Facebook, LinkedIn, and Uber have moved away from SQL for relationship data. Explore the fundamental concepts of knowledge graphs and understand how they outperform traditional SQL databases for complex relationship queries by up to 1000x. Set up a free Neo4j lab environment and work through hands-on tasks including connecting to the database, creating nodes and relationships, adding directors, performing bulk imports, and building a complete recommendation engine. Master the database structure that powers modern social networks, AI systems, and streaming platforms through practical coding exercises with Neo4j and Python. Compare SQL versus graph database performance and learn why graph databases excel at handling billions of interconnected data points with millisecond query times. Build a complete Netflix-style movie knowledge graph that connects actors, directors, and films, then implement recommendation algorithms similar to those used by major streaming services.
Syllabus
- The Facebook Problem: Why SQL Failed
- What is a Knowledge Graph?
- SQL vs Graph Database Showdown
- Setting Up Your Free Neo4j Lab
- Task 1 - Connecting to Neo4j database
- Task 2 - Create your first node
- Task 3 - Creating Relationships
- Task 4 - Add Director & Query
- Task 5 - Scale it up with bulk import
- Task 6 - Recommendation Engine
- Pro Tips & Best Practices
Taught by
KodeKloud