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!

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).

Based on the experience of wondering how facial recognition works in offline environments on-site, this course will guide you through building the basic structure of a facial recognition-based access and attendance management system using React + Electron and Python's FastAPI-based DeepFace. Rather than focusing on perfection, we focus on understanding the operating principles and laying the foundation for you to expand into your own personal projects.

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!

🔥 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.

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.

This course covers the entire process of evolving ChatGPT from a simple conversational AI into an intelligent AI Agent that performs real-world tasks. By utilizing the three core frameworks—LangChain, LangGraph, and LangSmith—you will build AI Agents that can be used immediately in practice.

This course explains the basic concepts of LLM and GPT in an easy-to-understand way for everyone. Students will build their own chatbot using the GPT API and deploy it on the web using Streamlit. By experiencing everything from the basics to hands-on practice, you can build a solid foundation for your first steps in utilizing AI.

It’s okay if you don’t know how to code. This course focuses on the experience of using AI to build an ad-revenue-generating Android app from scratch and successfully launching it in just one day. Many people stop at these stages: “I built the app, but how do I monetize it?” “I tried adding ads but got stuck on AdMob, policies, and reviews.” “I gave up right before launch because of the privacy policy.” In this course, we will navigate through every "drop-off point": 👉 Idea → App Creation → Ad Integration → Store Launch Essentials → Actual Deployment. We let the AI do the work, and we make the decisions. The goal is to complete an app with a "functioning revenue structure" within a single day.

This course is a hands-on masterclass that completely conquers the evolution of Diffusion Models through papers and code implementation. You'll learn the core models of generative AI, including DDPM (Denoising Diffusion Probabilistic Model) and DDIM, by studying the paper principles and implementing them directly. We analyze step-by-step the background of each model's emergence, mathematical formulations, network architectures (U-Net, VAE, Transformer), training processes (Noise Schedule, Denoising Step), and the ideas that led to performance improvements. Students will directly code all models using PyTorch, gaining not just paper comprehension but 'practical skills to reproduce and apply' them in real-world scenarios. Additionally, by comparing the differences between models and their developmental flow, you'll clearly understand how they expand and evolve. This course integrates theory, code, and practice into one comprehensive journey, providing researchers, developers, and creators alike with a systematic way to master the evolution of generative models. Beyond simply 'reading' papers, start your experience of 'understanding and recreating' through direct implementation now.

[2nd edition scheduled for completion in 2026] We explore how to create an AI judge by combining various agent frameworks such as CrewAI, LangChain, and AutoGen, which enable the implementation of LLM-based multi-agent technology, along with knowledge graphs and reasoning systems.

The Master Guide to AI for Java Developers! This course shatters the prejudice that AI is the exclusive domain of Python and empowers your Java applications with AI-driven eyes, ears, voice, and even coding capabilities. Grow into an AI Architect based on the OpenAI API. You will directly develop various AI experts such as an AI writer, translator, artist, and coding companion. You will also build a multi-functional AI assistant that integrates core features including text summarization, sentiment analysis, image description, Java code generation, speech-to-text/text-to-speech conversion, and image/subtitle generation. This is a golden opportunity to maximize the competitiveness of existing Java systems by learning how to assign AI roles through system messages and even implement harmful content moderation.

You will understand the present and future of AI technology, experience the testing process of AI models such as machine learning, and learn the role of a tester. You will gain a broad range of knowledge, from establishing AI-based system testing strategies to designing and executing test cases, as well as utilizing AI for test support. This course is based on the ISTQB AI Testing syllabus and provides an opportunity to perfectly prepare for the ISTQB AI Testing certification exam.

[Scheduled for completion of the 2nd edition in 2026] Explores the limitations of LLMs, the latest technologies to overcome them, and projected future technologies.

This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

Conquer everything about world-changing AI in just 4 lectures! Lecture 1. The True Identity of Artificial Intelligence AI is not magic. It's a digital brain created by analyzing human 'intelligence' like a mathematical formula! We thoroughly dissect the core structure of seemingly smart artificial intelligence. Lecture 2. Algorithm, AI's Creative (?) Thinking Method How does a pondering AI find answers? Experience firsthand the strategies of AI that plays Go, finds routes, and predicts your search results. Lecture 3. AI Hardware, The Engine That Turns Imagination Into Reality! The chip inside your smartphone is the heart of AI. We dissect everything from CPU, GPU, TPU, to even those unknown names. Lecture 4. The Great Clash of Machine Learning and Deep Learning! What on earth does it mean for AI to 'learn'? From classic rule-based AI to the currently hot ChatGPT! We trace the evolution of learning.

This is a lecture covering LLM theory and practical examples based on <Large Language Models, Just the Essentials!> (Insight, 2025).

[Source Code Provided] No coding knowledge required. Build it instantly in your browser using Google's latest tool (IDX) without any installation! Stop studying coding syntax! This is an ultra-fast, hands-on course where you'll build an RAG chatbot that perfectly understands internal company documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

"Your first step to creating a customized LLM with LoRA-based lightweight fine-tuning!" This is an introductory hands-on course designed so that even those new to LLMs can easily follow along. We minimize complex theory and guide you step-by-step through the entire process: loading the model → applying data → training → comparing results. In a short time, you'll directly experience the workflow of cutting-edge lightweight fine-tuning techniques like LoRA and QLoRA, and gain an intuitive understanding of "how LLM fine-tuning works." Even without extensive resources, experience the satisfaction of creating an LLM specialized for your domain!

Learn the core techniques of 'Prompt Engineering' to get exactly the answers you want from AI. From a complete beginner's first steps to expert practical applications, maximize your AI utilization skills!

LLM and Agent, the fundamental technologies behind AI like ChatGPT. LLM is currently the technology that has come closest to AGI. In this lecture, we will explore LLM and Agent technologies from a layperson's perspective.

Through this lecture, you'll be able to learn about the AI graduate school admission process and preparation methods from start to finish! I'll also share some great tips to increase your chances of getting accepted!

In an era of explosive data growth and crucial real-time processing, edge computing has established itself as an essential technology, no longer an option. This course is designed to systematically teach everything, from the core concepts of edge computing to deployment strategies for its application in real business environments. Through this course, students will firmly solidify the fundamental principles of edge computing and acquire practical knowledge and know-how applicable to real-world tasks and projects. Take the most certain first step towards becoming an edge computing expert, a core technology in the future IT environment!

AI proficiency determines your salary. Leave the tedious, repetitive tasks you do every day to AI. 'Almost Everything About Work Automation' teaches you how to create an automation system that handles your work on its own with just a few clicks, even without any coding knowledge. You will be freed from boring paperwork and data organization, and transform into an 'AI-savvy professional' who stays ahead of others.

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)