AI Data Pipelines with Spring
With Gregory Green
Liked by 18 users
Duration: 1h 37m
Skill level: Intermediate
Released: 9/25/2025
Course details
Description
What is this course about?
The lack of data integration is a common blocker preventing organizations from unlocking the power of artificial intelligence. Spring is a popular collection of projects that simplifies data integration and artificial intelligence development for Java applications. In this course, learn how Spring can be used to build data pipelines. Discover how Spring AI makes it easy to use AI models with the Java programming language. Understand how to build data pipelines with Spring Batch and Spring Cloud Streams using RabbitMQ. Explore how features within Postgres enable vector databases and machine learning for AI workloads.Instructor
Who teaches this course?
Gregory Green is an advisory solution engineer at VMware. He has worked as a senior software architect, developer, engineer, and consultant across industries including finance, telecommunications, and pharmaceuticals.Objectives
What will I be able to do by the end of this course?
- Develop AI data pipelines using Spring Batch and Spring Cloud Streams.
- Implement machine learning models in Spring applications using PostgresML.
- Utilize RabbitMQ to manage and stream data effectively.
- Deploy orchestrated AI workflows on platforms like Kubernetes.
- Perform similarity searches using vector databases.
Audience
Who is this course for?
- Data engineers
- Back-end developers
- Software architects
- Java developers familiar with Spring
- Technology enthusiasts interested in AI and data integration
Prerequisites
What do I need to know before taking this course?
- Proficiency in Java and understanding of the Spring Framework
- Familiarity with Postgres and SQL
- Basic knowledge of Docker and containers
- Experience with messaging systems such as RabbitMQ is helpful
Skills you’ll gain
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Meet the instructor
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Contents
What’s included
- Learn on the go Access on tablet and phone