Spring AI Generative AI Course Review: Build Real AI Apps with Spring Boot

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In-Depth: Developing Generative AI Applications with Spring

★★★★★

$79.99
$15.00  in stock

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Udemy.com

as of December 21, 2025 6:49 am

Mastering Spring AI and Advanced Generative AI Technologies

Created by: Ken Krueger
Technical Instructor in Software Development topics

Rating:4.79 (38reviews)     346students enrolled

What Will I Learn?

• Understand AI Fundamentals: Gain a solid foundation in essential AI concepts, including tokens, embeddings, semantic search, and vector stores.
• Explore Prompt Engineering and RAG: Learn about prompt engineering techniques and Retrieval-Augmented Generation (RAG) for improving AI interactions.
• Utilize the Spring AI project to effectively develop generative AI applications based on Spring Boot.
• Engage in Extensive Hands-On Labs: Participate in practical labs that provide direct experience with the Spring AI framework and foundational models.
• Handle Practical Programming Challenges: Learn best practices for storing access credentials, managing errors and retries, and setting custom parameters, etc.
• Utilize Key Parameters Effectively: Understand and apply common parameters like temperature, topP, max tokens, logit bias, and stop sequences.
• Emphasize Automated Testing: Incorporate automated testing practices to ensure the reliability and performance of generative AI applications.
• Gain practical experience working with OpenAI, Azure AI, Amazon Bedrock, Ollama, Anthropic, Cohere, Ollama, StabilityAI, and others.

Requirements

• Students should have basic proficiency in Java, including experience with the Spring Framework and Spring Boot. To complete the hands-on labs (recommended), students must also have access to a computer capable of running Java and an integrated development environment (IDE) of their choice, such as IntelliJ IDEA, Eclipse, or Visual Studio Code.
• Some hands-on labs require setting up accounts and credentials with AI model providers. These services may have associated charges, which are not covered by the course fee, though the overall cost is minimal.

Target audience

• This course is intended for software developers having basic, intermediate, or advanced knowledge of Java, Spring, and Spring Boot

Spring AI Generative AI Course Review

Introduction: Why This Course Deserves Attention

If you’re a Java or Spring Boot developer curious about how to create real-world Generative AI applications, the “Spring AI Generative AI Course” on Udemy is a must-consider. This course, titled “In-Depth: Developing Generative AI Applications with Spring,” brings together the power of Spring Boot and cutting-edge AI technologies like OpenAI, Azure AI, Amazon Bedrock, Anthropic, and more.

In this detailed Spring AI generative AI course review, we’ll explore what makes this program stand out — its content, teaching style, hands-on labs, pros and cons, and who should take it.

Course Overview: What You’ll Learn

This course bridges the gap between AI theory and Spring-based implementation. It’s structured to give developers both foundational understanding and practical expertise.
You’ll begin by mastering AI fundamentals — including tokens, embeddings, semantic search, and vector stores — before progressing into prompt engineering, Retrieval-Augmented Generation (RAG), and automated testing for AI applications.

Key Learning Outcomes:

• Understand AI fundamentals — tokens, embeddings, vector stores, and semantic search.
• Master prompt engineering & RAG to build smarter AI interactions.
• Use Spring AI Project to integrate AI into Spring Boot applications.
• Hands-on labs with real models from OpenAI, Azure, AWS Bedrock, Anthropic, Cohere, StabilityAI, and others.
• Learn to manage API keys, credentials, and errors while optimizing performance.
• Implement automated testing for robust AI applications.

With 8.5 hours of on-demand video, assignments, and a certificate of completion, this course offers a well-balanced learning experience for developers at all levels.

Who Should Take This Course

This course is tailor-made for:

• Java developers eager to add AI capabilities to their Spring Boot apps.
• Intermediate and advanced Spring Boot programmers who want to stay ahead of the AI curve.
• Professionals building chatbots, RAG systems, or AI-driven tools.
• Students and engineers looking to learn hands-on AI development instead of just theory.

A basic understanding of Java and Spring Boot is required. Some labs involve setting up credentials with AI providers (minimal cost may apply).

Why It Stands Out

Most AI courses focus on Python, but this course focuses on Java and Spring developers, which makes it unique. It introduces the Spring AI project — a powerful framework that simplifies connecting with foundational AI models.

You’ll learn not only how to call APIs but also how to design full-stack AI systems. From prompt engineering to retrieval pipelines, everything is covered with practical labs.

Moreover, the instructor does an excellent job of explaining complex parameters like temperature, topP, max tokens, logit bias, and stop sequences — so you can fine-tune your AI app’s behavior precisely.

Hands-On Learning with Real AI Models

What makes this course exciting is its lab-driven approach. You’ll build applications that connect to:

• OpenAI (ChatGPT & GPT-based models)
• Azure AI
• Amazon Bedrock
• Anthropic’s Claude
• Cohere
• Ollama
• StabilityAI

These labs simulate real-world enterprise scenarios. You’ll work with retrieval systems, vector databases, and RAG architecture, ensuring you can deploy real, production-ready generative AI systems.

Instructor’s Approach

The instructor follows a project-first teaching method. Every concept is reinforced with a coding demo or exercise. The pace is ideal — quick enough to stay engaging but deep enough for complex topics.

Each section ends with a lab challenge or assignment, which helps you apply what you’ve learned immediately. By the end, you’ll have built multiple Spring Boot generative AI applications that interact with various model providers.

Pros & Cons

Real-World Applications

The course content translates directly into practical skills. After completing it, you’ll be able to:

• Build AI-powered chatbots and assistants using Spring AI.
• Integrate vector search and embeddings for intelligent data retrieval.
• Implement RAG pipelines for accurate and contextual AI responses.
• Manage API keys and error handling in production AI environments.
• Use automated testing to ensure AI app reliability.

These are industry-relevant skills that are currently in high demand across software and enterprise AI development.

Why Developers Love This Course

Students consistently praise this course for:

• Its clear explanation of complex topics like embeddings and RAG.
• Code-along format that keeps learning interactive.
• Immediate real-world usability of concepts.
• Instructor’s practical insights from enterprise AI projects.

Whether you’re planning to build an internal AI assistant for your company or prototype a new AI SaaS product, this course gives you everything you need to get started.

Final Verdict

The Spring AI Generative AI Course on Udemy is a standout learning experience for Java and Spring Boot developers ready to explore the world of Generative AI.

By combining AI fundamentals with Spring integration, it offers a rare and valuable skill set that bridges traditional backend development with the new age of AI systems.

If you want to build generative AI applications using Spring Boot — not just understand them theoretically — this course delivers exactly what you need.

Rating: ★★★★★ (4.9/5)
Best for: Intermediate-to-Advanced Java Developers
Duration: 8.5 Hours of On-Demand Video
Platform: Udemy

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