We’ll Fill the Gap Instead of Experience — Practical System Design for Juniors in the AI Era

This is an 18-lesson course across 5 modules designed to transform Generative AI LLM agents—which often drain money through API costs—into a profitable structure by controlling expenses with model routing, cascading, caching, and loop guardrails. You will personally build everything from analyzing real-world cases of "cost bombs" to profit-and-loss simulations and architecture design projects. We recommend this course to AI developers and makers burdened by API costs, as well as those planning or operating agent-based services.

Messy code, a flood of requirements... If you're looking for a breakthrough with AI, Learn how to become a "high-performing developer" by leveraging AI in legacy environments, taught by the former VP of Engineering at Toss Payments. Legacy code isn't going anywhere, even in the age of AI. It’s no exaggeration to say that every company has legacy code, unless they were founded today. So, how should we utilize AI in this reality? In this course, the former VP of Engineering at Toss Payments, who led a large-scale payment service organization, demonstrates firsthand how to work effectively using AI in legacy environments. This isn't just a course about how to use AI or basic coding skills. The goal is to help you develop your "critical thinking" as a developer and truly understand what it means to work effectively.

This is a [Backend, Resume Enhancement] class prepared for job seekers and junior developers.

In an era where AI writes code for you, will you remain a 'Coder' or leap forward to become an 'Architect'? This course is designed for junior developers who can handle basic implementation but feel stuck about the next steps or are anxious about falling into the trap of 'fake experience'. We aim to go beyond simply learning clean architecture theory and turn Robert C. Martin's (Uncle Bob) high-level design principles into weapons for the AI era.

Developing an 'Autonomous' Premium Reservation Agent Backend Using Spring AI + JPA + MySQL Beyond Chatbots to Agents: The Standard of Tool Calling and Prompt Engineering

Through this lecture, you can learn about the characteristics and background of the Kotlin language, grammar and operation principles, usage examples, and things to be careful of when using Java and Kotlin together.

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.

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.

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

Building an 'Intelligent Collaboration' Expert Agent Team Using Spring AI Router Pattern + RAG + MCP Beyond a Single Agent to Architecture: The Standard for Router Patterns and Agent Isolation Design

Learn Springboot + Flutter RestAPI Board Creation Faster Than Anyone Develop a CRUD server with Springboot and create your own board with Flutter!!

This is a Kotlin coroutine lecture by the author of "The Definitive Guide to Kotlin Coroutines." This lecture covers everything from the basics to the core of coroutines. It provides various visual materials and clear explanations to help anyone easily understand asynchronous programming using coroutines.

Building a TodoList with Claude + IntelliJ - Complete MCP Mastery Master the workings of MCP by creating a TodoList with Claude and IntelliJ!

This is a full-stack hands-on course where you will implement a ChatGPT clone from scratch. From Spring Boot server to React frontend | Neo + Essential This is not just a course where you simply follow along with the code; it guides you through actual service deployment so you can build a high-quality AI chatbot service.

A Java advanced project course for beginner developers who want to develop practical skills! We'll build a console-based kiosk ordering system together using Spring Core, JdbcClient, and H2 DB.

Using generative AI tools such as ChatGPT and Claude, you will turn ideas into actual web services and experience the entire development and operations process in a single project—from Docker containerization and server deployment to domain connection, HTTPS implementation, and CI/CD setup. Rather than simply generating code, you will develop practical skills by completing and maintaining a service that real users can access.

This course focuses more on data modeling through entity design than on JPA technical explanations. Based on the principle that solid DB design is the foundation of application development, we analyze various design patterns—such as one-to-many, many-to-many, inheritance, and collections—alongside business scenarios. You will learn by directly observing the process of code being transformed into actual tables on screen. To ensure immediate practical application, we provide business use cases, source code, and test codes for each design pattern.

Regardless of the field! This is a lecture that covers the core fundamentals that developers must know in practice in an easy + code-oriented way. I highly recommend this lecture to all junior developers and job seekers who want to grow.

This is a text-based course that conducts mock interviews based on your résumé.

I highly recommend Spring AI to developers using Spring Boot and React, as well as those considering the introduction of AI systems in corporate environments. This course goes beyond a simple introduction to libraries; it helps you understand the core concepts and internal structure of Spring AI, and strengthens your practical implementation skills through various hands-on examples. The course is based on Spring AI version 1.1.x and provides continuous technical support and expansion strategies to ensure you can adapt to future version upgrades. Furthermore, we expand the practical value of Spring AI technology by utilizing MCP (Model Context Protocol) to achieve cross-domain context integration, AI linkage in distributed environments, and AI architecture design suitable for enterprise environments. With the goal of building AI systems that can actually be deployed in corporate settings, this will serve as a practical guide that balances theory and hands-on experience.

Through in-depth theoretical explanations of Kafka Connect and detailed practical training that can be used immediately in the field, we will help you grow into an expert in building data linkage and data pipelines based on Kafka Connect that are needed in the field.