Complete GenAI with Java & Spring AI: LLMs, RAG, AI Agents — 92% Off Coupon

Build production-ready Generative AI applications with Spring AI - LLM, RAG, AI agents, Chat memory, MCP, Observability

⭐ 4.6 out of 5 Rating (214 students) Created by Ali Gelenler, EA Algorithm Updated: April 20, 2026 🌐 English

Key Takeaways

A summarized snapshot of the essential course data, author credentials, and live coupon verification statistics from our manual technical audit.

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Course Title: Complete GenAI with Java & Spring AI: LLMs, RAG, AI Agents

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Provider: Udemy (Listed via CoursesWyn)

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Instructor: Ali Gelenler, EA Algorithm

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Coupon Verified On: April 20, 2026

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Difficulty Level: All Levels

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Category: IT & Software

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Subcategory: Spring AI

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Duration: 23h 30m of on-demand video

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Language: English

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Access: Lifetime access to all course lectures and updates

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Certificate: Official certificate of completion issued by Udemy upon finishing all course requirements

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Top Learning Outcomes: Learn and implement GenAI applications using Java and Spring AI · Learn how to call remote Large Language Models using Open AI, Google Gemini and Hugging Face APIs · Learn how to call local Large Language Models using Ollama and Docker Model Runner

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Prerequisites: Basic to intermediate knowledge of Java · Familiarity with Spring Boot · Experience with backend development concepts · Basic familiarity with AI/LLM concepts

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Price: $9.99 with coupon / Regular Udemy price: $129.99. Applying this coupon saves you $120.00 (92% OFF).

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Coupon: Click REDEEM COUPON below to apply discount

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What You'll Learn

The following technical skills represent the core curriculum targets for learners enrolling in this verified program today.

Learn and implement GenAI applications using Java and Spring AI

Learn how to call remote Large Language Models using Open AI, Google Gemini and Hugging Face APIs

Learn how to call local Large Language Models using Ollama and Docker Model Runner

Learn and implement Spring AI advanced concepts: Streaming, Structured output, Chat options, Advisors, Prompt templates

Learn Prompt engineering best practices including zero/one/few shot, CoT, changing creativity(temperature), controlled variability(top-p,) limiting tokens

Learn Prompt hacking techniques and their mitigation strategies: Prompt injection, Jailbreaking, Prompt leaking and Advanced hacking techniques

Understand GenAI and LLM fundamentals: Tokenizers, Embeddings, Positional encoding, Transformer architecture, Token prediction and Softmax formula

Understand chat memory and implement with multiple backends using Spring AI: In-memory and Jdbc for short-term memory, Vector store for long-term memory

Learn and implement multimodality using text, image and sound conversion use cases

Understand LLM limitations and their possible mitigations

Learn and implement advanced RAG systems

Learn and implement AI Agent systems with autonomous and chained workflow agentic systems

Understand MCP (Model Context Protocol) and implement MCP server and MCP client applications using Spring AI

Understand and apply Observability to RAG and AI Agent systems using Spring Observability

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Requirements

Please review the following prerequisites to ensure you have the necessary tools and foundational knowledge for this training.

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Basic to intermediate knowledge of Java

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Familiarity with Spring Boot

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Experience with backend development concepts

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Basic familiarity with AI/LLM concepts

About This Course

Comprehensive curriculum analysis and educational value proposition from the official provider library hubs.

Want to build real-world Generative AI (GenAI) applications with Java, Spring Boot, Spring AI, RAG and AI Agents—not just experiment with prompts?

This course will take you from fundamentals to production-ready AI systems, including RAG pipelines, AI agents, tool calling, chat memory, MCP, observability, prompt engineering, and prompt hacking.

Hi there! My name is Ali Gelenler. I'm here to help you learn GenAI using Java and Spring AI from fundamentals to real-world production ready AI architectures and systems with a practical approach.

In this course, you will focus on creating AI applications to go beyond AI generated code and implement over 20 use cases using Java and Spring AI together with various AI providers and models, such as Open AI, Google Gemini Vertex AI, Hugging Face, Ollama and Docker Model Runner. You will build AI applications and AI systems using LLMs (Large Language Models), integrate vector databases and embeddings, and design scalable backend architectures for Generative AI.

You will learn:

Building end-to-end GenAI systems in Java and Spring AI with advanced Spring AI concepts
Designing RAG pipelines with vector databases, embeddings, similarity search and semantic search using advanced ingestion and retrieval strategies such as query transformer, query expander, pre/post processors, re-ranker, metadata filtering and dynamic resource updates
Creating AI agents with tool/function calling using autonomous and chained workflow agentic systems
Implementing chat memory and long-term context with in-memory, jdbc and vector store backends using Spring AI advisors
Applying prompt engineering best practices and defend against prompt hacking techniques including prompt injection, jailbreaking and prompt leaking attacks
Using MCP (Model Context Protocol) for distributed AI systems, creating MCP Server and MCP client using Spring AI
Adding Observability (logs, traces, metrics) to AI applications
Learning Gen AI and LLM Fundamentals with Tokenizers, Embeddings, Positional encoding, Transformer architecture, Token prediction and Softmax formula
Mapping the Gen AI and LLM Fundamentals into practical solutions
Understanding LLM limitations and possible mitigations

You will implement 20+ real-world use cases, including:

AI-powered assistants: Summarizer, Java Doc generator, Programming helper, Email drafter, Post generator
Document Q&A systems with advanced RAG pipelines
Security review from architectural diagram AI agent system with multiple tools including Remote Mcp Server tool, Web tool, RAG tool and Diagram extract tool, implementing both autonomous and chained workflow agent systems
Multimodal applications including Image-to-Text, Text-to-Image, Speech-to-Text and Text-to-Speech use cases
Order status helper with advanced chat memory strategies
Production-ready AI systems with monitoring and tracing

Technologies & tools you will use:

Java & Spring AI
Advanced Spring AI concepts: Streaming, Structured output, Chat options, Advisors, Prompt templates
OpenAI, Google Gemini (Vertex AI), Hugging Face APIs
Ollama & Docker Model Runner for local LLMs
Vector databases using PgVector
MCP (Model Context Protocol) with MCP Server and MCP Client implementations
Observability tools (Grafana, Prometheus, Otlp, Tempo, Jaeger, Loki and Promtail)

This is a practical and production-oriented course. You will not just generate code using AI tools—you will learn how to:

Design systems
Handle real-world limitations
Build scalable and maintainable AI applications

For more detailed information on the progress of this course, you can check the introductory video and free lessons, and if you decide to enroll in this course, you are always welcome to ask and discuss the concepts and implementation details on Q/A and messages sections. I will guide you from start to finish to help you successfully complete the course and gain as much knowledge and experience as possible from this course.

Support & updates

You can ask questions anytime in Q&A
The course will be continuously updated as Spring AI evolves
You’ll get guidance to fully understand and apply concepts

Remember! There is a 30-day full money-back guarantee for this course! So you can safely press the 'Buy this course' button with zero risk and join this learning journey with me.

Meet Your Instructor

Academic background and professional track record of the subject matter expert responsible for this curriculum.

Ali Gelenler, EA Algorithm

Verified Architect

A global leader with specialized excellence in IT & Software. Instructors are vetted for curriculum quality, responsiveness, and consistent student success across the Udemy platform.

4.8 / 5.0

Instructor Rating

94% +

Success Rate

Course Comparison

Market-relative value analysis comparing this verified instructor deal against professional subscription and retail averages.

Feature Benchmarks	This Verified Offer	Global Standard
Cost Verification	FREE (100% Validated)	Fixed Subscription Fee
Enrollment Type	Professional Lifetime Access	Limited Time Ownership
Certification Award	Included with Access Code	Required Add-on Fee

Expert Review

Andrew Derek

Lead Course Analyst, CoursesWyn

"After auditing the curriculum depth and verifying the live access protocol, Complete GenAI with Java & Spring AI: LLMs, RAG, AI Agents stands as an essential career asset. For a verified cost of $0, the return-on-learning ratio far exceeds commercial alternatives."

✅ Strategic Advantages

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Official Certificate: Credential generated at no cost.
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Mobile Friendly: Full access via smart TV & mobile.
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Expert Pacing: Modular design for professional schedules.

❌ Considerations

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Technical Depth: Requires focused 10+ hours study.
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Tool Prep: Certain labs require proprietary software setups.

Verification Outcome: Exceptional Academic Value

Course Rating

Collective learner data and performance analytics based on verified alumni feedback loops and technical graduation audits.

4.6

★★★★★

Verified Excellence

5 Stars

88%

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1 Stars

Frequently Asked Questions

Curated answers to the most frequent learner inquiries regarding availability, certification, and enrollment logic protocols.

Andrew Derek

Expert Reviewer

Andrew Derek is a lead editor and course analyst at CoursesWyn with over 8 years of experience in online education and digital marketing. He meticulously audits every Udemy coupon and course syllabus to ensure students get the highest quality learning materials at the best possible price.

Contact Andrew • Verified by CoursesWyn Editorial Team

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