It’s OK if you only know HTML/CSS/JS! A hands-on project completed with React and Firebase

Learn how to measure the performance of your React-built web services and optimize them for speed and efficiency.

Let's quickly learn React's core design patterns through concepts and examples!

This is an introductory course to the front end using Next.js and Tailwind CSS. It is designed to complete static deployment without a backend, so even beginners can experience the satisfaction of completion.

This is a project-based course where you build a “ToDo List” app from scratch using React + TypeScript with a practical, real-world approach. Rather than simply learning syntax, you’ll develop a feel for using TypeScript by completing the app in the form of a real service—from designing the component structure, managing state, and applying types to implementing features, integrating local storage, and deploying the app.

You can easily learn Nuxt UI, Nuxt SEO, Nuxt Server Api, Pinia, PWA, Firebase, Email Login, Google Login~~

In this 24-hour tutorial, you will learn how to build your own YouTube clone. We will cover advanced topics such as Next 15 and React 19 (including tRPC), prefetching in Server Components, utilizing Suspense in Client Components, video processing, background jobs, and AI features.

"Becoming a Developer Who Excels at React" has been published. This book provides a solid foundation by systematically guiding you from the basic principles of the web needed before learning React to the latest React hooks. Through over 40 diverse hands-on projects and abundant practical examples, you can apply theory directly to real-world situations and develop problem-solving skills. Additionally, it helps you grow into a developer capable of building high-quality React applications by learning essential modern web development technologies such as Redux Toolkit, Zustand, and Firebase.

A portfolio-focused course on deploying a React frontend and Spring Boot backend directly to the AWS cloud! This course is helpful for those who want to quickly deploy frontend and backend projects for their portfolio. You will gain the necessary knowledge for deployment through short-term, step-by-step practice, covering everything from server configuration to Docker, domain connection, Nginx, and HTTPS application!

We will create a Twitter-like SNS service using the React & Next & Redux & Redux-Saga & Express stack. Finally, we will perform search engine optimization and deploy it to AWS.

We have entered an era where it has become incredibly easy for web developers (especially React developers) to launch apps. With Expo, you can release both Android and iOS apps even faster. Let's become developers who can quickly launch apps through Expo.

"Why did the AI write this code?" or "Why can't it remember what I just said?" The frustration you encounter when using AI tools like Claude Code stems from not knowing how the tool actually works. This course flings open that black box. Over 25 lessons, we will build our own Coding Agent from scratch that functions exactly like real-world professional tools—giving the LLM 'eyes' to see files (Read), 'hands' to fix code (Edit), and 'feet' to execute commands (Bash). This isn't just about learning how to use a library. You will gain hands-on experience by implementing code to understand how AI perceives project structures, why it loses its memory during long conversations, and how to solve those issues technically (Sliding Window, Summary). Through this process, you will evolve from being a mere 'user' of AI tools to an 'AI provider' who understands the underlying principles and can customize and evaluate tools to fit your specific needs.

This is a hands-on web development project course where you complete everything from planning and design to implementation and deployment using generative AI. You’ll create designs with Stitch and Figma Make, generate code with AI Studio, and deploy it as a real service. Even if you don’t know much about coding, you’ll learn how to develop alongside AI and complete your own AI web app. Now you, too, can become a developer who collaborates with AI.

Solidify your foundation in Python/Django web service development. Learning Django takes time, but you can maximize your productivity through iterative development. Turn your imagination into reality.

We invite you to become a ‘Top-Tier Enterprise AI Systems Architect’ Do not remain a micro-level technician (Prompt Writer) who merely assembles libraries created by others or polishes prompt sentences. From mathematical first principles to runtime control-loop kernels and autonomous recovery infrastructure — through 40 years of practical engineering insight that has driven industrial operations in South Korea, I will firmly guide you to become a top-level ‘Enterprise AI Systems Architect’ who protects your company’s business and digital sovereignty. Now, begin the great journey of transforming uncontrollable AI into a perfect industrial core. “Why does an AI that ran perfectly in a demo start spouting strange nonsense or bring the pipeline to a halt as soon as it is deployed to production?” “Why do AI projects that so many companies launch with great enthusiasm ultimately fail to escape the ‘PoC (Proof of Concept) swamp’ and get abandoned?” These are the most desperate questions that countless developers and systems architects I have met in the field have asked me. Hello. I am Hongjip Kim, who spent more than 40 years in the powertrain R&D division of the South Korean automotive industry (including 17 years as an executive in Hyundai Motor Group R&D), led the export of engine and drivetrain technologies worth 130 billion won, and commanded operations as the CEO/CTO of a listed mid-sized manufacturing company. From the perspective of an engineer who has spent decades in mechanical engineering and precision-control environments, a ‘risk of fatal uncertainty’ lurks behind today’s frenzy to adopt generative AI. In mission-critical industrial environments where even a mere 0.1% error or mistake can directly result in the destruction of physical equipment worth hundreds of millions of won and an enterprise-wide shutdown, integrating a probabilistic chatbot that simply relies on probability to generate plausible text directly into a service is like carrying a ticking time bomb into a fire. This course was designed to impart the “practical engineering methodology for training uncontrollable probabilistic AI into the most robust industrial control core, one that allows not even 0.000% of syntax errors.” 1. The 3 Major Fatal Bottlenecks You Face in the Field (Problem) Many engineers attempt to challenge production environments using an approach limited to one-off prompt tuning (Vibe Prompting), only to become frustrated when they encounter the following 3 structural defects: Finite Context and ‘Lost in the Middle’: As conversations or multistep executions grow longer, critical system instructions are pushed aside and the context window is exhausted, causing the system to lose its memory and amplifying hallucinations. Nondeterministic Outputs and Cascading Pipeline Collapse: Tiny probabilistic fluctuations, such as one missing closing bracket in JSON or an incorrect type, can paralyze legacy ERP/CRM API calls and destroy data integrity. Untrusted Code Execution and Infrastructure Security Bankruptcy: When scripts autonomously generated by an agent run in a non-isolated host OS environment, they create risks such as kernel escapes and sensitive-data leakage. As such, AI malfunctions in industrial environments are not merely quantitative accuracy problems; they become a massive financial disaster in the form of asymmetric business loss (Asymmetric Business Loss). 2. ‘How’ to Solve These Problems Perfectly (Solution) This course differs fundamentally from commercial courses that teach only how to use fragmented off-the-shelf tools. By combining 40 years of hands-on field expertise with computer systems engineering, it delivers 3 hardcore architectures for vertically integrated, system-level control of probabilistic AI: ① Move Beyond Prompting to ‘LLM-OS & Context Orchestration’ Following Andrej Karpathy’s paradigm, redefine the LLM not as a conversational respondent but as the central computational core (CPU) of a computer. Systematically organize the context window as ultra-low-latency volatile RAM, the internal vector DB as Disk, and external APIs as an I/O bus. Through MemGPT hierarchical virtual-memory paging, preserve critical state without saturation even during infinite conversations, while scaling a dynamic agent network through MCP-based Liquid Swarm MAS, minimizing token costs. ② ‘Deterministic Harness Engineering’ That Constrains Probabilistic Hallucinations to 0.000% Leave the language model’s creative flexibility open only during the Reasoning phase, while firmly confining the physical output layer that interacts with external systems using mathematical Boolean algebra and compilers. Apply EBNF / XGrammar-based CUDA logit masking to forcibly block the generation probability of invalid tokens at P = 0.000%. Form a physical security isolation ring so that code generated by agents runs only once inside a Firecracker MicroVM micro-virtualization sandbox with 5ms snapshot restoration capability. ③ ‘High-Reliability MLOps·LLMOps Autonomous Recovery Infrastructure’ Without Wasting GPU Resources Build vLLM PagedAttention and S-LoRA hot-swapping to suppress idle VRAM waste to below 4%. When a multi-agent API fails, restore data consistency 100% through SagaLLM reverse compensation transactions. Through an OpenTelemetry/Langfuse distributed observability network, defend system availability by executing an unmanned automatic canary rollback whenever a decline in the RAGAS faithfulness score (Data Drift) is detected. 3. Practical Value That Drives Spiral Growth (Pedagogy & ROI) This course is systematically designed according to the 5 levels of Bloom's Taxonomy. Starting from simple theoretical recall (Remember), learners directly code and validate a 5-stage debugging pipeline (analyzing deceptive baseline trap source code ➔ deconstructing adversarial engineering ➔ establishing a Robust integrity pipeline ➔ calculating the TEI ROI formula ➔ SOTIF/ISO 42001 governance). Going beyond the intuitive satisfaction of simply “working well,” I will apply the Forrester TEI (Total Economic Impact) financial model to visualize, from an executive perspective, how much the AI system you build reduces your company’s rework cost (Rework Cost), avoids failure risks worth hundreds of millions of won, and proves an ROI of more than 200%.

Building your own emotional diary service with Spring AI + React It's time for our 4th project with Neo + Essential!

This is mission content for a development project. We provide a PRD planning document, Figma designs, and API endpoints so that you can practice by implementing a timer app called DevTime yourself. Make the knowledge you have learned completely your own by implementing a project at a level similar to an actual service 🚀

"A Hands-On Web Development Project Course: Complete the Entire Process from Planning, Design, and Implementation to Deployment Using Generative AI" Starting from brainstorming ideas, we’ll create designs instantly with AI, build a fully functional website with React, and deploy it to the internet—we’ll complete the entire process together, step by step. The latest AI tools, such as Stitch and Figma Make, will assist with the design work, and we’ll guide you through complex coding in easy-to-follow steps.

This is a hands-on course that takes you through completing a Flutter mobile app from start to finish using the CLI and AI. You’ll experience the entire development cycle, including Firebase authentication and data management, AI API integration, monetization through AdMob ads and in-app purchases, and deployment to a real Android device. Even with limited development experience, you’ll learn how to use AI to request specific features and improve them, building the practical skills needed to release a polished app.

No more AI toy projects that end with a single API call! Based on my experience designing and deploying a full-stack AI chatbot, I will guide you through the entire process of building an AI chatbot that "works as a real service"—covering streaming, tool calling, memory, multi-modal capabilities, and Human-in-the-Loop.

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!