Practical Introduction to RAG: Completing Vector Search with pgvector

This is a hands-on introductory course where you can learn everything from Kafka installation to Producer/Consumer message transmission by following along with Spring Boot. Rather than focusing on complex theories, you will quickly understand the basic flow of Kafka—how messages are published and subscribed to through Topics—by writing and executing actual code yourself. It is suitable for beginner and junior backend developers who are integrating Kafka for the first time.

This course goes beyond explaining the concepts of Spring Batch and covers how to actually integrate Spring Batch into a service that is already running. Based on structures used in real-world practice, you will learn by directly implementing everything from Batch Job configuration and execution flow to data processing structures. Rather than simple examples, it provides step-by-step explanations based on professional architectures, covering Batch Job configuration, execution flow, and data processing structures. In particular, we focus on: How to connect Batch to an existing Spring Boot service and how to build a structure that can be operated stably. Through this course, you will: ✔ Be able to build Batch directly into existing services ✔ Be able to design large-scale data processing structures ✔ Reach a level where you can apply these skills immediately in the field 👉 This is not a "theory lecture" 👉 This is a practical course on integrating it into actual services

This course is for those who want to learn DDD but feel lost on "how to apply it to a real project." In this course, we will implement DDD design from start to finish by **building an actual ordering system** based on Spring Boot. The focus is not on simple theory, but on "structures and code that can be used immediately in practice." After taking this course, you will be able to: ✔ Design DDD-based projects on your own ✔ Implement professional-level structures yourself

AI agents can fail due to various reasons, including data errors, security threats, increasing costs, and system integration issues. This course examines major obstacles and failure cases that occur during the AI agent implementation process and explains practical strategies for design, inspection, and operation to prevent them. Through this, you can understand the risks and limitations of AI agents and establish appropriate implementation directions and stable operational standards for your organization.

RAG (Retrieval-Augmented Generation) from theory to the latest multimodal and agent-based RAG! This is a hands-on lecture designed to be understandable even for non-majors. From paper reviews to practical code implementation, it's designed so that even those encountering RAG for the first time can easily follow along.

Master the complete lifecycle of building modern Generative AI applications using Large Language Models, Retrieval-Augmented Generation, and Agentic AI systems. Learn to design enterprise-grade AI solutions from prompt engineering to deployment, combining LLMs with vector databases and external knowledge sources for production-ready applications.

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.

Forget boring lectures that end with nothing but grammar! An ultra-compressed practical roadmap for developers of other languages to build and deploy a production-level Go API server in just 3 hours.

You will learn about RAG, VectorDB, LangChain, OpenAI, sLLM, and fine-tuning, which encompass the most important AI-related technologies at this time.

This course is for those who want to learn DDD but feel lost on "how to apply it to a real project." In this course, we will implement DDD design from start to finish by **building an actual ordering system** based on Spring Boot. The focus is not on simple theory, but on "structures and code that can be used immediately in practice." After taking this course, you will be able to: ✔ Design DDD-based projects on your own ✔ Implement professional-level structures yourself

This is a tutorial-style Claude code development course that even beginners and those new to development can easily follow. Based on experience teaching offline classes for planners, designers, and non-developers, you can learn everything in a single flow—from basic examples not covered in books to intermediate development projects. Using Claude code, you will experience the step-by-step development process, starting from "Hello World" to a Lucky Draw app, a device-optimized cafe menu management web page integrated with Claude design and Excel data, and finally a SaaS web application that can be uploaded to databases and cloud services. Tutorials are provided in stages of theory, practice, and projects. Through six levels of hands-on exercises, you will master AI-collaborative development methodologies and experience the entire development cycle, including cloud deployment and operation.

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.

This is a practical backend course designed to cultivate the service planning and design thinking skills that developers need in the AI era.

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.

The days of feeling relieved by black-box code spat out by AI are over. By piercing through the physical limitations of computers and the inner workings of the Node.js core engine, we provide you with the engineering control to remain unshakable in the face of any traffic surge.

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.

Even people who are studying Java for the first time can easily understand it. You'll learn Java through theory with rich explanations and hands-on practice.

You use ChatGPT, but haven't you found it difficult to explain why it gives certain answers? "I know terms like RAG, Agents, and Fine-tuning... but it's hard to explain them accurately." "I get tongue-tied whenever I hear LLM-related terminology." "Conceptual explanations are always vague during AI meetings." This course was created specifically for people like you. This is a theoretical course designed to help you understand LLMs not just as a 'tool,' but as a 'structure.' It doesn't teach you how to use ChatGPT or Gemini; instead, it establishes the foundation so you can explain exactly why they work the way they do.

We design and implement AI agent systems that go beyond simple chatbots to perform tasks autonomously. From Sense-Think-Act loop-based architectures to LangGraph cyclic structures, RAGAS and LangSmith-based quantitative evaluation, and operational guardrails, you will complete your enterprise-grade agent engineering capabilities through hands-on practice of the entire process.

In this course, you will be able to create a Reddit website from scratch, step by step.

This course goes beyond simple CRUD-level database usage to help you acquire PostgreSQL skills necessary for the AI era from a practical perspective. Based on AI development experience in Silicon Valley, you will learn step-by-step how to design and utilize JSON, indexes, transactions, and even pgvector in real-world services, while mastering methods to solve complex data structures and performance issues.

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.

You can learn about the core functions of MySQL and how to effectively use them in your work. You can also gain a new understanding of important parts that you have been using for a long time and have overlooked, and gain in-depth database knowledge.