Spring AI in Practice: Implementing Chatbots, RAG, and MCP in Spring Services

The most definitive practical guide for developers who want to integrate AI into their Spring projects right away! Beyond simple LLM API calls, you will perfectly master building production-level AI environments that can be immediately applied to real business logic using RAG and MCP.

(5.0) 4 reviews

59 learners

Level Beginner

Course period Unlimited

Spring Boot
Spring Boot
Elasticsearch
Elasticsearch
vector-database
vector-database
LLM
LLM
RAG
RAG
Spring Boot
Spring Boot
Elasticsearch
Elasticsearch
vector-database
vector-database
LLM
LLM
RAG
RAG

What you will gain after the course

  • Building a 'stable and scalable AI chatbot' that is perfectly integrated into the Spring ecosystem, going beyond a simple 'external LLM API call'

  • The ability to build a 'practical, customized RAG system' by integrating Elasticsearch Vector Store, moving beyond the limitations of hallucinations.

  • An experience with 'MCP (Model Context Protocol) based agents' that go beyond simple text generation to actively interact with external APIs and systems

  • Completion of a 'commercial-grade AI backend architecture' that seamlessly integrates with existing Spring Boot business logic

Current backend recruitment trends!
You don't still have zero experience with AI service integration, do you?🥶🥶

I am JSCODE Sini, who started as a developer and has served as a bootcamp instructor for 5 years,
producing over 200 developers.


Just looking at the atmosphere in companies these days,
"Shouldn't we introduce AI to our service too?", "Has anyone tried integrating AI features?" they keep looking for backend developers who know how to handle AI.
Now,
AI integration capability has become a mandatory survival spec, not an option.

I completely understand that feeling of wanting to say, 'I should add this to my Spring project too,'
only to feel overwhelmed because everything you find is a Python reference and
the AI terminology is so unfamiliar.🥺


That is why I created this course—to help Java developers new to AI technology
gain the 'AI backend construction experience' that will become their most powerful weapon in the job market,
and to enable them to master RAG·MCP systems tailored to the familiar Spring framework and practical environments (Elasticsearch)
in a short period of time.


Practice is better than a hundred words!
Rather than spending days just studying difficult infrastructure concepts,
it is fastest to implement it yourself with code and apply it to a real-world project.


Job Posting Example



👍 Recommended for the following people:

I'm new to AI integration.
Those who know how to write backend code with Spring but have never introduced AI features into a project.

I feel overwhelmed just looking at AI terminology!
Those who aren't familiar with concepts like LLM and RAG, but want to take this opportunity to dive in and properly integrate AI into their projects.

I feel overwhelmed looking at job postings.
Those who cannot confidently answer the "Preference for LLM/RAG-based service construction" requirement in recent job postings.



🎯 The goal of this course is clear.

The goal is for backend developers new to Spring AI to
quickly learn how to integrate AI services for practical use,
and to be able to directly build RAG and MCP agents that provide accurate answers using their own data
by leveraging Spring AI and Vector Databases.


Now, I hope you can confidently share your experiences without being flustered when an interviewer asks, 'Can you build LLM or RAG-based services?'
Do you want to properly study how to implement AI services using Spring?

Are you anxious because you feel like you're the only one without AI credentials in this rapidly changing world?


If so, I hope you take this course to lower your fears
and firmly grasp only the core concepts essential for practical application.


I'll see you in the lecture. ☺️



🍀 What will you achieve after this course?

  • Escape from being an 'AI Backend Novice' and gain technical confidence
    You will gain the confidence of a practitioner who can design, integrate, and stably operate Spring-based AI architectures without being flustered by sudden AI feature implementation tasks or hallucination issues where the AI provides incorrect answers.

  • Acquire essential concepts for immediate practical use
    Instead of getting lost in vast AI modeling theories, you will master only the core concepts and operating principles essential for practical backend developers, such as Spring AI, RAG, MCP, and Elasticsearch(Vector DB).

  • Customized Problem-Solving Skills for Real-World Scenarios
    By learning how the concepts you've acquired are applied in real-world customer service chatbots or customized AI search logic using internal data, you will be able to immediately build and apply AI features to existing services.


  • Grasp the core flow of CI/CD deployment automation
    Beyond simple prompt input, you will experience reading the flow of AI architecture by understanding the overall mechanism of how a user's request passes through a Spring server, interacts with the LLM and external systems (vector stores), and is completed into an intelligent response.



🧑‍🍳 A quick taste of the lecture!

'What are Embeddings?' lecture video

'Testing with Swagger UI' lecture video

'Data Preprocessing for High-Quality RAG' lecture video

'MCP Client Development' lecture video



✔ Notes

This course is conducted under the assumption that you already have basic knowledge of Java and Spring Boot.


However, please note that even if you lack some of these concepts, we have included
supplementary explanations and code comments to ensure you have no trouble with the hands-on practice.



💬 What if you have questions while listening to the lecture?

If you have any questions or find something difficult to understand while listening to the lecture, please use the
Question Board (Q&A Board) or the 1:1 Open KakaoTalk Room to ask!🤩


I will check and provide an answer as quickly as possible.



👩‍💻 There are many practitioners who write good code, but educators who make code easy to understand are rare.

A practitioner is someone who writes code well.


However, an educator is someone who ponders day and night why the code was written that way and
how to convey the code to students in the easiest possible way.


There are many experts in the field, but
often when you actually listen to their explanations, they are so difficult that you find yourself tilting your head in confusion.
This is because they focused more on listing knowledge rather than on the weight of education.


If you receive the wrong education, the learning process itself becomes painful,
and it ultimately leads to undesired results, wasting precious time and opportunities in your life.


I want to be more than just an 'instructor' who simply passes on skills; I want to be a
'teacher' who contemplates your career and life together with you.

The power to turn complex concepts into our own language rather than jargon,
that is my pride as an educator.

Please take a look at the path I have walked and my sincerity,
and make a careful decision for your precious future.



💚 Let me introduce myself!

Hello! I am JSCODE Sini.
It feels like only yesterday that I was dragged to a major class by a friend in college,
but I've already been developing for nearly 10 years.


At first, I wanted to make a positive impact on the world through the programs I created.
However, as time passed, I gained one firm realization.


'Rather than creating services myself,
wouldn't properly nurturing one talented developer have a much greater impact on the world?'


If the developers I've taught create wonderful services in their respective positions,
that positive influence will grow exponentially.


With that single mindset, I have trained over 200 developers in the field at boot camps over the past 5 years.
(* Produced successful candidates for Line, Kakao, and Kurly ☺️)


Seeing my students grow as they enter the industry,
I feel the power and fulfillment of education every single day.


Now, I intend to meet you beyond the offline classroom, in the wider online world.


I want to help you grow into a 'capable developer' who creates new value by unsparingly sharing the skills and know-how I have accumulated in the field
so that you can achieve your own growth.


I sincerely hope that this lecture, prepared with great care,
brings a pleasant change to your development career! 🙌



🎖︎ Student Best Review

** This is a review written for the previous course <Introduction to Spring Batch: Basics of Large-Scale Processing in 3 Hours>.



** This is a review written for the previous lecture <Log Management and Monitoring - ELK, Prometheus, Grafana>.




🚌 Feeling lost about which order to take the courses in?

'[2026] Essential Curriculum for Getting a Job as a Backend Developer (IT Service Companies)' Please refer to this!

Recommended for
these people

Who is this course right for?

  • Those who have no prior knowledge of AI but want to take this opportunity to study it thoroughly from the basics.

  • Those who are looking to introduce AI features to a backend project for the first time

  • Those who want to go beyond simple LLM API calls and apply AI features directly to real-world web services

  • Those who want to learn the AI service architectures recently in demand in the field, such as Chatbots, RAG, and MCP.

  • Those who want to clearly highlight their "experience in enhancing services using trendy, cutting-edge AI technology (Spring AI)" on their resume.

Need to know before starting?

  • Java Basic Knowledge

  • Spring Boot Basic Knowledge

Hello
This is synee

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Courses

Key Experience

  • National Core Network Management: Expert in operating and optimizing Supreme Court and Public Procurement Service systems

  • Next-Generation Public Platform Construction: Intelligent NEIS Application SW Development and Architecture Design

  • Full-stack Education Expert: Transferring practical skills through numerous lectures, including K-company bootcamps

  • Enterprise Solution Expert: Possesses capabilities in large-scale system maintenance and advanced architecture design


Hello! I'm Sini from JSCODE, who started as a developer and is now active as an educator.

I have personally built and operated critical national systems, but what I am actually best at is "explaining those difficult concepts so that anyone can understand them."

The actual field is naturally rough and complex. 🤯

But there's no reason the learning process has to be that way, right?

It doesn't matter what stack you want to learn right now.

I will break down the complex technologies of the actual field and feed them to you in a way that is very easy to understand! 🍀

Let's start the amazing experience of turning the complex ideas in your head into actual working services, easily and fun together with me!

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75 lectures ∙ (7hr 18min)

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