Music Recommendation Backend with Spring Boot and Neo4j
Learn how to build a Music Recommendation Backend with Spring Boot, Neo4j, Spring Cloud, and Collaborative Filtering
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What You Will Learn!
- Introduction to Backend Development: Understand the basics of backend development and the role it plays in building complex applications
- Spring Boot Fundamentals: Dive into the world of Spring Boot and learn how to rapidly develop powerful and scalable backend applications.
- Neo4j Graph Database: Explore the fundamentals of Neo4j and discover how graph databases can revolutionize data modeling for your music application.
- Implementing Collaborative Filtering: Learn the principles behind collaborative filtering and how to implement personalized music recommendations for users.
- Spring Cloud for Microservices: Understand the concepts of microservices architecture and leverage Spring Cloud to build a scalable and resilient backend.
- Cipher Queries with Neo4j: Master the art of crafting secure and efficient cipher queries to interact with Neo4j and optimize your database operations.
- User Authentication with Keycloak: Implement secure user authentication and authorization using Keycloak to ensure the privacy and security of your users' data.
- Real-World Application Development: Apply your knowledge in a hands-on manner by building a fully functional music backend application throughout the course.
Description
Welcome to "Building a Music Recommendation Backend," a comprehensive Udemy course that takes you on a journey to create a robust and real-world music application using cutting-edge technologies. This course is designed for intermediate to advanced developers who want to dive into backend application development and explore the power of Spring Boot, Neo4j, Spring Cloud, Collaborative Filtering, Cipher Queries, and Keycloak.
What You'll Learn:
Introduction to Backend Development: Understand the basics of backend development and the role it plays in building complex applications.
Spring Boot Fundamentals: Dive into the world of Spring Boot and learn how to rapidly develop powerful and scalable backend applications.
Neo4j Graph Database: Explore the fundamentals of Neo4j and discover how graph databases can revolutionize data modeling for your music application.
Implementing Collaborative Filtering: Learn the principles behind collaborative filtering and how to implement personalized music recommendations for users.
Spring Cloud for Microservices: Understand the concepts of microservices architecture and leverage Spring Cloud to build a scalable and resilient backend for your music application.
Cipher Queries with Neo4j: Master the art of crafting secure and efficient cipher queries to interact with Neo4j and optimize your database operations.
User Authentication with Keycloak: Implement secure user authentication and authorization using Keycloak to ensure the privacy and security of your users' data.
Real-World Application Development: Apply your knowledge in a hands-on manner by building a fully functional music backend application throughout the course.
Who Should Take This Course:
Developers looking to enhance their backend development skills.
Those interested in exploring the world of graph databases and Neo4j.
Individuals eager to build a real-world music application using modern technologies.
Anyone aiming to understand collaborative filtering for personalized content recommendations.
By the end of this course, you'll have the skills and knowledge needed to create a sophisticated music recommendation backend, and you'll be well-equipped to tackle similar challenges in real-world application development. Enroll now and embark on your journey to becoming a proficient backend developer!
Who Should Attend!
- Developers looking to enhance their backend development skills.
- Those interested in exploring the world of graph databases and Neo4j.
- Individuals eager to build a real-world music application using modern technologies.
- Anyone aiming to understand collaborative filtering for personalized content recommendations.