How to Work with Claude — From Practical Workflow Automation to Vibe Coding

Claude Code is rapidly growing as one of the most powerful AI coding agents available today. However, simply installing Claude Code is not enough to maximize productivity. To truly utilize Claude Code effectively, you must understand advanced features such as context management, memory systems, skills, subagents, and agent teams. In this course, we will learn step-by-step, starting from the installation and initial setup of Claude Code to advanced workflows used in real-world practice. Students will learn how to integrate Claude Code with VS Code and how to select and utilize various models. Furthermore, you will master how to perform complex development tasks efficiently using Context Engineering, Memory management, Skills, Subagents, and Agent Teams. After the course, you will be able to use Claude Code not just as a simple AI chatbot, but as an AI development partner that genuinely boosts development productivity. Based on real-world experience in AI development and software projects, the instructor explains how to apply Claude Code to practical work and helps students solve common issues such as context management problems, token waste, and inefficient prompt writing.

This is a practical course that uses Codex to connect business planning, website creation, marketing materials, task organization, and email automation. Even if you are not a developer, you will learn how to delegate tasks to AI and refine the results using Notion, Linear, Figma, and Google Workspace in an actual workflow sequence.

This is a practical introductory course designed to help general office workers utilize generative AI as a business partner rather than just a simple tool. The objective is to develop the ability to use AI safely while complying with security and copyright standards, based on an accurate understanding of its operating principles and limitations. From the core principles of prompt engineering to streamlining text-based tasks such as planning, reporting, emailing, and minutes-taking, as well as Excel data analysis and the use of images and PDF documents, students will learn step-by-step. This helps drastically reduce time spent on repetitive tasks and secures the practical capability to handle multiple roles. Beyond individual use, the course covers how to build team-level work templates and standards. It is an action-oriented curriculum designed to ensure that participants possess work automation assets that can be applied immediately to their jobs after completion, leading to productivity improvements across the entire organization.

Even if you don't know coding, you can read data—everything about no-code AI analysis that makes work sense explode! From marketing to HR and quality management—we'll make your work sense explode with AI.

Have AI document its decisions and reasoning in the project wiki every time it works, safeguard that wiki, and check it to ensure it doesn’t break months later. Build the disclosure alert bot for real, establishing rules one by one whenever something goes wrong.

Do you want to create your own blog and social media content, but find Figma difficult and design overwhelming? In this course, you will learn everything from Figma's basic interface and frames to handling images, text, shapes, and effects step-by-step by creating actual content. You will produce blog covers, thumbnails, CTA elements, and digital business cards. Furthermore, you will complete reusable content templates using Components, Auto Layout, Properties, and Variants, allowing for quick edits even when text and images change. Go beyond simply creating a single pretty image—build your own content production system that can be used consistently for your blog and social media. Point 1. Master Figma basics through actual content creation - Learn core functions such as frames, layers, images, text, and shapes through practice-oriented lessons. - Understand the Figma workflow by directly creating blog covers and thumbnails. - Even non-designers can naturally acquire basic skills while completing their own projects. Point 2. Create content templates that allow for repetitive edits - Learn the core principles of Components, Auto Layout, Properties, and Variants. - Create thumbnails and CTA elements where text, colors, and images can be swapped quickly. - Minimize the time spent starting from scratch every time you create content. Point 3. Build your own content pipeline - Create design assets that can be utilized across multiple channels like blogs and Instagram. - Establish a consistent channel image by registering color, text, and effect styles. - Complete a foundation for sustainable content production by repeatedly utilizing the templates you built yourself.

We solve problems that are difficult to answer with practical research experience and proven prompts.

Even if you are not a major or a designer, you will learn how to directly create and modify web UIs, proposals, and design systems using Claude Design and Figma. To ensure immediate application in practice, the course proceeds step-by-step with a focus on hands-on practice—covering everything from the differences between Claude Code and Claude Design to installation, plugin utilization, component-based UI production, design modification, and methods for applying them to live services. This lecture is designed to help developers, planners, and marketers who found design tools difficult to experience rapid result-making through AI and component-based workflows.

This course is designed step-by-step, from the basics to practical application, so that even those new to Claude AI can easily follow along. In this course, you will start with the basic concepts of Claude AI and how to write prompts, and then learn various use cases such as document writing, summarization, translation, brainstorming, and file and image analysis. You will also practice how to create documents, charts, diagrams, and simple applications using Claude Artifacts, as well as creating infographics using Claude Design, modifying results, and saving them as PDFs. Finally, we provide productivity-enhancing know-how that can be used immediately in the workplace, including advanced prompt engineering techniques, automating repetitive tasks using the Projects feature, Excel functions, and coding support. From beginners with no AI experience to office workers, students, and content creators who want to increase work efficiency, the course explains everything through practical examples so that anyone can learn easily and apply it right away.

Learn how to use chatGPT in practice to dramatically increase your work productivity, and apply it directly to your work, from document writing to data analysis!

"Beyond Data Analysis: From Predictive Model Design to Optimization (29 Lectures in Total)" Have you finished your data analysis but feel stuck when it actually comes to building a model? We help you fully master not just how to call libraries, but the working principles of each algorithm and optimal model validation strategies.

A practical AI automation series that plugs directly into your work If you’ve learned about AI but still feel unsure how to use it in your work, what you need now isn’t an explanation of features, but practical ways to use AI that immediately transform your work. The SMART WORK ORDER series is a hands-on AI automation series designed to reduce repetitive tasks across roles—including marketing, planning, HR and general affairs, sales, customer support, data analysis, and team leader and manager responsibilities—and turn them into real work deliverables. Content drafts, meeting minutes, proposals, consultation scripts, FAQs, VOC reports, data analysis reports, team prompt libraries, and more. Each course is designed not as a “lecture you watch and understand,” but as a hands-on program where you follow along and create actual deliverables. The prompts and templates you learn today can be applied to your work tomorrow, expanding into practical assets that improve not only individual work speed but also team productivity. An AI-powered transformation of work that reduces repetitive tasks and raises the quality of deliverables. SMART WORK ORDER is a role-specific, practical AI program that changes the way you work to make it faster, more accurate, and smarter.

This course is a 37-lesson, approximately 14-hour program that covers OpenAI’s AI coding agent, Codex, from start to finish. AI coding tools are now commonplace. However, most users remain at the level of accepting autocomplete suggestions or asking questions in a chat window. Agentic tools like Codex can do much more than that. They can read an entire project, modify multiple files simultaneously, run tests, and find and fix errors on their own. The problem is that they require an equivalent level of control. If you do not know what to allow and what to block, or how to teach the tool your project’s rules, you will end up cleaning up the code it creates afterward. This course focuses on how to establish that control. In the beginner section, you will learn installation and your first conversations, file editing and session management, and slash commands, while building a foundation in prompt writing. Through hands-on practice, you will internalize three principles: making clear requests, breaking down tasks, and verifying the results. The intermediate section is where the main content begins. You will configure behavior with config.toml, teach project rules with AGENTS.md, and manage memories with Memories. You will design safety boundaries yourself by combining the sandbox with four types of approval policies. The course then covers thread separation and parallel work, planning mode, connecting MCP servers, and creating custom skills based on SKILL.md. Finally, after covering web searches and Git automation, VS Code and Cursor integration, and hands-on FastAPI practice, you will examine Codex’s internal protocol, the SQ/EQ queue model. Understanding how the tool works changes how you respond when problems arise. The entire course follows the process of building a single service called TaskFlow. Rather than learning each feature in isolation, you will experience, in sequence, when and why each one is needed in a real project.

Copilot Chat will become more than just a simple AI assistant - it will be your reliable work secretary that maximizes your productivity and creativity. In this course, learn Copilot Chat's core features and usage methods, practical cases that can be applied immediately to real work, and customized tips tailored to each task, and start experiencing how your way of working changes with Copilot Chat!

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.

Evolve Obsidian beyond a simple notepad into a personal knowledge database, and build an AI assistant that understands your notes and documents using Claude Code. Create your own workflows to automate repetitive tasks, completing a knowledge system where your daily work and learning compound over time and transform into your own unique expertise.

Have you introduced AI but still find yourself losing time to repetitive tasks? The problem isn't the AI; it's the 'system.' This course guides you through the process of building a team of six AI assistants—including an executive assistant, content assistant, marketing assistant, CRM assistant, and personal productivity assistant—all using Notion AI. Based on my experience automating hundreds of repetitive tasks in real-world business settings, we will build actual workflows from start to finish, covering everything from organizing notes and automatically generating meeting minutes to blog writing, CRM construction, and automated KakaoTalk notifications. After completing this course, you will have a system where your own AI assistant team works automatically, powered solely by a Notion Business plan.

This covers how to use ChatGPT not merely as a question-and-answer tool, but as a thinking tool for structuring problems and comparing and validating multiple possibilities. Instead of memorizing prompt formulas, you will learn the workflow of collaborating with AI through actual conversations and practice the entire process—from defining the problem and separating roles to comparison and validation—in 30 minutes.

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!

If you receive stock recommendations from AI and leave the timing of buying and selling to it, will you actually make a profit? AI is not a prophetic tool that predicts future stock prices. Instead, it can be a powerful investment assistant that checks the emotions swaying your investment decisions, analyzes complex information, and helps you stick to long-term investment principles. In this course, you will understand the typical behavioral errors of individual investors—such as loss aversion, panic selling, and FOMO—and learn how to create unwavering investment criteria using AI prompts and investment analysis tools. From back-calculating target assets to portfolio design, utilizing tax-saving accounts, and setting up automated recurring purchases, complete your own AI investment system that even busy office workers can consistently execute. Point 1. Understand the limits of AI investment and use it properly Understand through data why AI is not suitable for stock recommendations and predicting trade timing Utilize AI in areas it excels at, such as earnings call analysis, ETF overlap diagnosis, and portfolio reviews Learn how to review counter-scenarios and risk factors so you don't just believe optimistic answers Point 2. Correct the malfunctions that sway investment psychology Diagnose recurring investment behavior patterns such as loss aversion, the disposition effect, panic selling, and FOMO Practice the 72-hour rule to reduce impulsive trading and routines for formalizing selling conditions Design AI prompts that help maintain long-term investment principles despite market volatility Point 3. Create a long-term investment system that sustains itself automatically Design a recurring investment plan and portfolio based on target assets and investment periods Review investment strategies through Monte Carlo analysis and tax-saving account simulations Complete an investment structure that executes without constant deliberation by setting up automated purchases and cash buffers