Practical Agent Development: Where Kakao PlayMCP Meets Spring AI

An AI system that grades and reviews your code in 5 seconds - imagination becomes reality. This course is an all-in-one project that builds a **'GitHub PR Automatic Analysis and Grading Bot'** using Spring AI. When a student submits an assignment (Pull Request), the server detects it and AI analyzes the code changes (Diff). The grading results are then stored in the database, feedback is automatically posted as GitHub comments, and students can check their results on a dedicated dashboard. From backend to AI integration and frontend (Vaadin) - all with Java! This is the ultimate introductory guide for all developers who want to complete their own AI service from A to Z.

# Building an 'Intelligent Collaboration' Expert Agent Team Using Spring AI Router Pattern + RAG + MCP Beyond Single Agents to Architecture: The Definitive Guide to Router Pattern and Agent Isolation Design

Spring AI + JPA + MySQL Premium Reservation Agent Backend Development with 'Autonomous Behavior' Beyond Chatbots to Agents: The Definitive Guide to Tool Calling and Prompt Engineering

Developing AI Applications with Spring Boot and Spring AI: Mastering OpenAI for Real-World Solutions

Learn the most important communication part of the Internet of Things (IoT). You can learn the core contents of the overall communication that transmits, collects, processes, and monitors center data. Through this course, you can design an IoT communication prototype before making a prototype, and use it for various projects and competitions.

[TPC DB!] A course that allows you to learn database modeling while thinking, learn database modeling step by step, and master everything from database modeling to web programming implementation all at once.

This course is a step-by-step course that allows you to learn and understand what the WEB MVC framework is and how the WEB MVC framework has been transformed into the Spring WEB MVC framework through the TPC (Think-Express-Code) technique.

You can improve your Java programming skills by working on your own projects using various Java APIs and Open APIs.

We have completed a backend bootcamp course implemented by various institutions into a single curriculum. This lecture is a bootcamp pre-training (P) lecture. Anyone can take it, and those who want to take advanced learning should apply for the bootcamp (ZM) course.

Through training in thinking, expressing, and coding, you can easily understand and approach Java programming. You can understand the relationship between programming elements and gain confidence in future Java API utilization and projects through precise concept organization of object-oriented programming.

This course is a step-by-step course that allows you to learn and understand what the WEB MVC framework is and how the WEB MVC framework has been transformed into the Spring WEB MVC framework through the TPC (Think-Express-Code) technique.

[Spring 2nd Edition] is a course to create a backend (Java Backend) development expert with integrated capabilities by directly implementing a Spring Legacy project to perfectly implement reply posting, paging processing, and search functions among bulletin board functions, and a bulletin board project using Spring boot, Spring JPA, and Security.

In [스프1탄], through step-by-step learning from Spring Framework to Spring Security, it is a course that creates backend (Java Backend) development experts who build web-based ERP systems.

# Building an 'Intelligent Collaboration' Expert Agent Team Using Spring AI Router Pattern + RAG + MCP Beyond Single Agents to Architecture: The Definitive Guide to Router Pattern and Agent Isolation Design

An AI system that grades and reviews your code in 5 seconds - imagination becomes reality. This course is an all-in-one project that builds a **'GitHub PR Automatic Analysis and Grading Bot'** using Spring AI. When a student submits an assignment (Pull Request), the server detects it and AI analyzes the code changes (Diff). The grading results are then stored in the database, feedback is automatically posted as GitHub comments, and students can check their results on a dedicated dashboard. From backend to AI integration and frontend (Vaadin) - all with Java! This is the ultimate introductory guide for all developers who want to complete their own AI service from A to Z.

This course is a hands-on program for implementing generative AI applications based on text, images, voice, and documents using the OpenAI API. Starting from setting up the Anaconda and Jupyter Notebook environment, it covers essential development environment configurations for practical work, including API Key management and understanding costs and tokens. Based on the latest Responses API, you'll implement text generation, summarization, classification, Vision (image understanding), voice processing, and PDF input processing, while practicing core features used directly in the field step-by-step, such as Function Calling, Structured Outputs (Pydantic), Embedding, and RAG (File Search). Additionally, including Web Search, Code Interpreter, Streaming, Background tasks, and Conversation State management, you'll learn how to expand beyond simple API calls to 'intelligent AI services'. Finally, the goal is to implement agent-based AI systems that autonomously select and execute tools using the Agents SDK and MCP (Model Context Protocol), while learning the structure and design perspectives necessary for actual service development.

Even if you don't know coding, you can read data - everything about no-code AI analysis that makes perfect sense! If you can use Excel, PPT, and Google Sheets, AI will now handle data analysis for you.

In the AX era where AI technology and UX design converge, what strategies should product teams use to design customer experiences? A 17-year veteran senior researcher from a major corporation and knowledge sharer with a PhD in HCI will share insights based on the latest trends, use cases, and research findings.

This course is designed to teach the entire process of 'AI Training Data Construction,' which is essential for successfully executing AI modeling projects. Learners will not simply remain at the theoretical knowledge level, but will experience step-by-step the data construction processes required in actual practice. Specifically, the course covers the entire process from AI training data planning → acquisition → storage → preprocessing → labeling → pseudonymization and transformation through hands-on practice, structured to develop practical skills that can be immediately applied in the field. Additionally, learners will systematically study the most important data management capabilities in AI projects, such as data quality management and security issues, personal information de-identification processing, and dataset optimization. Through this, learners can grow from simple data collectors into data specialists who can proactively plan and execute AI projects. 👉 Through this course, learners will understand how to construct high-quality training data that determines AI model performance and acquire practical capabilities to effectively apply this in real work environments.

This course covers the entire process of designing and implementing generative AI services centered on LangChain 1.0 and LangGraph through step-by-step hands-on practice. Beyond simple LLM calls, you'll directly implement operational AI system architectures that include agent-based architecture, state management, memory, streaming, middleware, and Human-in-the-Loop. Through hands-on practice with document/PDF/web data-based RAG systems, SQL Agent (Chinook DB), tool-calling-based Agents, Supervisor pattern multi-agents, and state machine-based workflows using LangGraph Graph API, you'll build reusable agent pipelines that can be immediately applied in real-world scenarios. Additionally, through structured output (Pydantic-based), agent middleware (Summarization, HITL, Retry, PII protection), and token/step-by-step streaming, you'll complete generative AI applications with the stability, scalability, and controllability required in actual services. 👉 For those who want to accurately understand the internal structure and execution flow of LangChain/LangGraph 👉 For those who want to implement RAG·Agent as a real service structure, not just a "demo" 👉 This is the optimal course for those who need a realistic practical roadmap covering state-based agents, SQL·document automation, and multi-agent orchestration.

Kotlin Programming Language, which you can learn by practicing with 76 examples. You have to develop in Kotlin starting tomorrow, but you don't have time to study the grammar? Let's quickly learn all the grammar of Kotlin with the examples provided in this lecture.

Automate Creating YouTube Shorts with AI!! Learn from scratch how to automatically create YouTube Shorts with n8n. Build a complete workflow that runs from text→image/music→video creation→upload all at once. Practice distinguishing between test mode/production mode and tips for saving costs. Complete 3 ready-to-use automation templates by the end of the course. Learn step-by-step from node placement so you can follow along even without coding knowledge. Let's automate AI YouTube Shorts production together!

AI Work Automation + Side Income Generation with Just One Click!!! Make, the ultimate work automation tool - have you been hesitating to start due to its complex settings and features? Build the automation you've been dreaming of with step-by-step lectures that even beginners can easily follow.

The Latest Trend in Generative AI, AI Agents! How to Stay Ahead with Cursor, which handles all development tasks, and MCP, which expands functionality!

Through this lecture, you will be able to build a backend server using the hottest language, Rust.

"Let's put an end to Spring Batch. Putting a stop to the dark ages of batch code.💀"

Are you lost while learning web development? I'll help you find your own way. Even if you're not from a computer science background, you can understand how web service architecture works through a short 1-hour lecture.

Learn the easiest way to handle AI with Spring AI. Let's learn Spring AI by building a RAG chatbot.

For those who want to introduce OpenSearch and ElasticSearch to AWS services, we will show you quick results centered on AWS OpenSearch software.

This lecture covers how to easily implement game backend systems using UGS (Unity Gaming Service). You will practice essential features such as Guest and Username/Password authentication, game data storage, leaderboards, and Remote Config. UGS has built a perfect ecosystem with Unity, preparing a practical course for easy learning without entry barriers, allowing immediate application to your projects.

Excel, coding, app development—anyone can start easily with AI. Learn from Excel automation to Python basics and app creation through hands-on practice using generative AI tools like ChatGPT and Perplexity.

Beyond basics like API design, CRUD implementation, and JWT authentication, all the way to backend architecture design! This is an introductory system design course to help you build 'your own backend architecture' that you can confidently discuss in interviews.

Are you confused about which technology trends really matter among the flood of information? We've analyzed global reports from Gartner, Microsoft, and others to clearly explain 10 key technologies (multi-agent systems, physical AI, AI security, etc.) that will define 2026.