This is a practical course where you can learn how to build a company website yourself using React, Node.js, and MongoDB. Let's build a full-stack project together with a basic background in React and Node.js!

This course starts with the question "If I had been on the Titanic, could I have survived?" and completes a full-stack project that develops an AI model to predict survival probability based on actual data and serves it as a web service. You'll practice the entire process of AI and web development, from deep learning modeling using PyTorch, building a backend server with FastAPI, to implementing a user interface with Next.js.

This is a practical course where you will directly create a timer app using React, Electron, and Zustand, and even deploy it to cross-platforms (Windows, macOS, Linux). Starting with familiar React web development, you can learn the entire flow of desktop app development, including global state management via Zustand and final GUI deployment!

In this course, you will practice step-by-step using React and FastAPI to implement social features like real-time voting, comments, and likes, as well as integrating payment systems (KakaoPay, TossPay, etc.) for monetization.

This course covers the fundamentals of the Notion API and teaches you how to automate Notion by integrating AI (Claude) using Notion MCP. You'll learn to directly control blocks, pages, and databases by following the official API documentation, and ultimately complete a hands-on project that creates databases and automatically adds pages by analyzing text file content using only natural language commands (prompts).

🔥 Build a customized platform for Hanja learning! Leverage Google Gemini AI and Firestore to directly implement your own Hanja vocabulary book, stroke order animation, and even handwriting recognition!

🔥 Firebase User Authentication Completed with just HTML + Tailwind CSS + Pure JavaScript! From social login to phone and location verification, easily and quickly build an account system without a complex backend.

Now it's time to take on a real-world challenge 🔥 We will develop a production-grade SNS using React.js + TypeScript + Supabase, building features such as authentication & authorization, infinite scroll, image uploads, likes, infinitely nested comments, and dark mode. In the process, we will also explore server and global state management techniques using Zustand and Tanstack Query.

This course conducts hands-on practice related to Diffusion models among generative artificial intelligence models. By reading and implementing the prompt-to-prompt paper, which is a representative Diffusion model application paper, we expect to cultivate the ability to understand the latest artificial intelligence papers.

Learn how to implement integrated regular and social logins using Spring Boot and React. Build a login system in both MPA and SPA environments and practice JWT and OAuth2 authentication. Understand and implement the entire login flow through example projects applicable directly to real-world scenarios.

The real world is unforgiving. I will thoroughly pass on my optimization expertise through a meticulous mission system, showing you how to design smooth user experiences even in extreme environments where tens of thousands of real-time data points pour in. Go beyond simply writing code and leap forward to become an irreplaceable senior engineer who dissects performance through understanding engine principles.

This comprehensive course teaches you how to build any full-stack application using AI tools like Cursor AI, Claude Code, v0, ChatGPT, and Replit. Learn coding basics, front-end and back-end development, database integration, debugging, and deployment. Perfect for beginners and anyone looking to leverage AI to build real web and mobile apps quickly and efficiently.

Build and deploy community applications using the MERN Stack (MongoDB, Express, React, Node + Firebase)

What to Expect from This Course Welcome to LangGraph in Action, your ultimate guide to mastering the design and deployment of advanced AI agents using LangGraph. In this course, you’ll explore the fundamentals of building modular, scalable, and production-ready agents, all with a hands-on approach. From understanding the basics of LangGraph’s state-based design to creating a full-stack application, you’ll gain the skills needed to bring AI agents to life. Course Highlights State-Based Design: Dive into LangGraph’s core philosophy of nodes and edges to create structured, maintainable agents. Memory Management: Explore short-term memory with checkpointers and long-term memory with the Store object to enable agents that adapt and learn. Advanced Workflows: Build human-in-the-loop systems, implement parallel execution, and master multi-agent patterns. Production-Ready Development: Learn asynchronous operations, subgraphs, and create full-stack applications using FastAPI and Docker. By the end of the course, you’ll not only have a strong theoretical understanding but also the practical skills to deploy AI agents anywhere, entirely with open-source tools. Whether you're a developer aiming to stay ahead of the curve or a seasoned engineer looking to expand your AI toolkit, this course equips you for the rapidly growing field of AI agents. With the increasing adoption of AI agents in real-world applications, this course ensures you're prepared to design, build, and deploy advanced systems that solve practical challenges. Let’s start building and shaping the future of AI together!

This course is Part 3 of the Full Stack lecture series, designed to help you solidly master the latest server technologies and Docker. The course is structured to enable you to practically incorporate Docker into your tech stack by meticulously testing Docker's various options, learning related technologies such as Linux that are necessary for understanding Docker, and building actual complex services.

This is a practical course where you will directly create a timer app using React, Electron, and Zustand, and even deploy it to cross-platforms (Windows, macOS, Linux). Starting with familiar React web development, you can learn the entire flow of desktop app development, including global state management via Zustand and final GUI deployment!

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.

This is a DevOps course based on practical experience in Silicon Valley. It goes beyond theory to cover content that can be applied immediately in the field. You will learn how to develop using Generative AI (Vibe Coding), set up CI/CD tools in a Kubernetes environment, and implement strategies to keep operating costs at $0. We will cover configuring a production environment without additional costs by running DB, Redis, S3, and batch jobs inside Kubernetes, and you will master building automated pipelines using GitHub Webhooks and Jenkins through hands-on projects.

Traditional React development and Next.js development are completely different approaches. This course penetrates the core of the latest Next.js 16 and teaches you the 'real' Next.js way of development. Experience how to achieve both performance and efficiency, from job portfolio projects to real-world projects. Let's develop the Next.js way! The course is structured to help you learn by doing, creating actual examples to understand how to apply Next.js features. You'll learn faster through actual code rather than theory, focusing on Server Components and covering Server Actions and caching strategies. Since the goal of the course is to catch up with the Next.js vibe as quickly as possible, the lectures are conducted using JavaScript. However, each lecture's examples are additionally provided as course materials created in TypeScript. December 18, 2025 - Updated to Next.js 16

A portfolio-focused course on directly deploying React frontend and SpringBoot backend to AWS cloud! This course is helpful for those who want to quickly deploy frontend and backend projects to their portfolio! You'll be able to practice step-by-step in a short period the knowledge needed for deployment, from server setup to Docker, Domain connection, Nginx, and HTTPS implementation!

AI is no longer a choice, but a matter of survival. Reduce development that took 3 days to 30 minutes, delegate repetitive tasks to AI, and focus on solving more important problems. With AI-native development methods that you can apply immediately in real work, not just theory, we'll show you the definitive way to be recognized as a "developer who's good at AI" at your company.

In the era of swift execution and validation, execute faster than anyone with VIBE Coding! Achieve complete monetization, from ads to payments, all by yourself.

This explains the foundational principles of large language models like ChatGPT with a focus on theory.

Mastering Model Context Protocol (MCP) is a practical, engineering-focused course designed to help developers build real, secure, and production-ready AI backends. After helping thousands of students overcome confusion around LLM integration, tool calling, and backend architecture, I created this course to solve the most common problems: “How do I build a reliable backend that LLMs can call safely?” “How do I choose between SSE, stdio, or streamable-http?” “How do I scale MCP into real applications with FastAPI, Auth0, and LangGraph?” “How do I structure my MCP tools, resources, prompts, and context?” In this course, I guide you step-by-step—from spinning up a minimal MCP server to deploying a fully secure, Dockerized system. Every lesson is hands-on, designed to remove complexity and give you a clear, repeatable workflow for building modern AI systems. If you're frustrated by vague tutorials and want a clear, concrete, engineering-level understanding of MCP, this course is built for you.

Developing an AI Safety Report Service with React + Spring AI The 5th Neo + Essential project lecture is about building a Safety Report system, an idea for improving government systems!

This course covers practical strategies for leveraging AI in the machinery and metal processing industry to enhance productivity and quality. It analyzes key process data from CNC, welding, cutting, and other operations, explaining how AI technology is applied to reduce defect rates, enable predictive maintenance, and manage worker safety through real-world case studies. Learners will understand AI-based processing optimization methods that can be immediately implemented in the field, from small and medium enterprises to large corporations, and gain insights to realize manufacturing innovation in global competition.

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.