Claude Code in Practice: From AI Development Workflows to Project Deployment

Explore → Plan → Implement → Commit. Master a proven AI development workflow with Claude Code. Learn everything from MCP and sub-agents to prompt engineering through 23 missions, and complete 3 real-world projects.

While LLMs are currently transforming the development environment, what truly matters is not just "writing code on your behalf" but integrating them as features into a service. This course provides a step-by-step guide to implementing a lightweight yet polished Tarot reading service using Next.js and the OpenAI API. In the first stage, we will build an MVP that works without a backend, connecting the user input flow (questions/threads/card selection) to result generation. In subsequent stages, we will expand the functionality by building a backend, implementing general login and OAuth, adding community features, and creating a reading dashboard. Finally, we will conclude by deploying to AWS and integrating Google AdSense to complete a service ready for actual operation. Additionally, we will cover understanding pricing structures and cost optimization strategies to ensure that LLM API usage costs do not become a burden.

This course teaches non-developers how to properly build, operate, and monetize a service using Claude Code. It provides template repositories and operational know-how so that non-developers and beginner developers alike can use Claude Code at the level of the top 1% of developers. This course will be especially helpful for those who want to build a service with Claude Code at a truly “professional developer” level; those who want to create a service capable of generating revenue through a one-person business or side project; those who have built something powered by an AI agent like Claude Code but are stuck because they lack the know-how to operate it properly; and those who feel overwhelmed as their solo project grows because bugs keep occurring and things become difficult to control whenever they add new features. The course also covers how to build a foundation for monetization and provides guidance on operating the service under the assumption that real customers will be using it. Once you have actual customers, processes such as monitoring errors occurring on the production server, server status, and logs are essential. However, there are surprisingly few places that teach these processes. In my course, along with this kind of detailed and professional operational know-how, I also explain how to enable AI to observe these monitoring metrics and data and take appropriate action.

A selfish era where only those who know how to properly utilize AI can generate profit. Essential web development concepts for profitability and a realistic guide you must know to 'properly' direct AI coding agents. From the mindset of coding without writing a single line of code to realistic methods for building a product with zero budget, and even practical details on business registration and tax processing. This is an AI-driven profitable web programming guide filled with insights gained from the actual field.

: "From environment setup to 7 practical projects, a deep learning full-stack journey across data domains (35 lectures in total)" Go beyond simply following example code and learn how to cook various types of real-world data using deep learning. Starting from building CPU/GPU development environments, you will cover waste sorting classification (Image), stock price prediction (Time-series), ECG anomaly detection (AE), animation stylization (GAN), medical image segmentation (U-Net), and sound classification (Audio)! Systematically master core deep learning algorithms through hands-on projects.

Simple tutorials alone make it difficult to apply in practice. I will clearly pass on my professional know-how, covering complex state management and multi-agent design methods.

Build a Saju (Four Pillars of Destiny) analysis AI agent that integrates Manseryeok, Astrology, Zi Wei Dou Shu, Onomancy (Name Study), and MBTI using n8n workflows and Python algorithms. We will complete a production-level service system from start to finish where 13 specialized agents collaborate to generate professional-grade Saju reports.

AI is only as good as you are. Learn vibe coding properly in three steps: how to use AI → essential foundational knowledge → project development. For those who want to learn vibe coding the right way, we deliver the core concepts that remain unchanged regardless of which AI you use, broken down into bite-sized pieces.

The starting point for a successful AX (AI Transformation) is not technology, but the leadership's understanding of AI. This course is designed to help executives grasp the overall flow of AI easily and clearly, while covering ways to maximize business productivity through the familiar Google Workspace and Gemini. Moving beyond mere theory, we provide 5-minute hands-on tasks for each session and a 1:1 customized online meeting (30 minutes) with AX Cody to systematically guide your company's tailored AI adoption strategy.

Can you create a service with your ideas even if you don't know how to code? With AI, it is possible! In this course, you will experience the entire process of turning an idea into a real web service using "Vibe Coding" tools used in the industry, such as Gemini, Lovable, Antigravity, Cursor, and Claude Code. You won't just learn how to use the tools; you will master a new way of service development in the AI era—from planning and deploying to integrating payments. Point 1. Master 5 Core Vibe Coding Tools - Hands-on practice with core features and applications of Gemini, Lovable, Antigravity, Cursor, and Claude Code - Understanding the Vibe Coding development method of collaborating with AI Point 2. Building a Real Service Without Coding - Hands-on process of planning and implementing a book recommendation web service - Understanding the entire service creation flow: Idea → Development → Deployment Point 3. Practical Skills for Service Launch and Operation - Understanding domain purchase, server setup, and the deployment process - Learning core operational technologies such as payment module integration and SEO settings

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.

Does changing it on the screen mean it’s been saved? From server responses and data persistence to login and permissions, AI responses and performance, and validation and deployment—this is Part 2 on what else you need to decide and verify before releasing an AI-generated interface to real users.

You can learn the core concepts of complex Next.js in a short time. We'll teach you only the essential practical knowledge for those learning Next.js for the first time. Captain Pangyo's new Next.js course, who has been conducting framework courses for 8 years. You can learn the coding and learning methods of "Frontend Developers in the AI Era"! 😊

This course teaches the essential CS knowledge required for web development using AI. If you don't understand the principles of servers, databases, and deployment, "Vibe Coding" will inevitably hit a wall at some point. Through interactive textbooks, you will quickly learn essential concepts, enabling anyone to complete a web project using Vibe Coding.

Have you ever actually run a service you built? Deployment and observability, external integrations and queues, files and extensions, and operating AI features. This is Part 2, where you learn what else needs to be decided to keep an AI-built backend serving real users continuously.

Even if the SQL is written correctly, is your data still protected in production? Access and permissions, recovery and safe changes, scaling and replication, MongoDB, Redis, DynamoDB, and search. This is Part 2, where you’ll learn what else needs to be defined to uphold the data standards established in Part 1 in production and across other storage systems.

The screen created by AI looks plausible, but can you actually use it from start to finish? Learn how to find missing conditions in HTML, CSS, JavaScript, state, input, and navigation—and what screen requirements to give the AI and what criteria to use when reviewing the results.

The course consists of a practical curriculum that can be immediately applied to the field, ranging from how to use the latest agent tools such as Genspark and Manus to corporate security guidelines. Through this, you can directly build an AI agent collaboration system that automates repetitive tasks such as information gathering, data analysis, and basic report writing.

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.

"The cost of making one app is the price of a cup of coffee." Learn vibe coding with Kimi K3, an open-weight model with 2.8 trillion parameters. You’ll launch your first app in a browser with a single sentence, create a UI by providing a hand-drawn sketch, and have it build and deploy an entire full-stack web app to the internet. If you’re already using Claude Code, you’ll also learn how to keep that environment as-is and simply switch the model to K3. It’s pay-as-you-go, not a monthly subscription. In an actual test, one session that created and deployed an app cost 1.69 dollars. 14 lessons, approximately 102 minutes total; the course is free.