[ Linux in the AI Era ] - Getting Started with Linux the Right Way

Instead of theory and memorization, you will naturally master 50 basic Linux commands through practice-oriented learning where you type and execute them yourself. With 95% of the entire course dedicated to hands-on practice, you can gain muscle memory for essential practical functions such as file management, permission settings, and process control. The goal is not to memorize commands, but to become familiar with Linux.

In the era of AI, the way we learn programming must also change. Now, the ability to collaborate with AI is more important than writing code yourself. However, to communicate with AI, you must understand basic syntax such as variables, loops, and functions. This course consists of 95% live coding and focuses on learning Python basics through hands-on practice. This is an introductory Python course designed not just to write good code, but to help you communicate better with AI.

We will examine the major OT security threats that can occur at production sites in the food and pharmaceutical industries, focusing on real-world cases. You will understand what security issues can arise in smart factories, production facilities, quality control systems, and traceability management processes, and learn basic response methods to prevent production shutdowns and data falsification in a way that is easy for beginners to follow.

We will completely resolve the anxiety of those who felt frustrated by blindly copying AI-generated code without understanding the internal workings of HTTP or the causes of unexpected hanging.

Feeling overwhelmed by where to start with AI auditing? AI has moved beyond a mere technology trend and is rapidly expanding into corporate decision-making, workflow automation, customer service, recruitment, security, and risk management. However, compared to the speed of AI adoption, not many people systematically understand questions like: "Is the AI being properly controlled?", "Can we trust the AI's judgment?", or "What risks could arise from the data, models, and operational processes?" In particular, those working in IT auditing, security, internal control, and project management often face these concerns: - How does AI auditing differ from traditional IT auditing? - Is it enough to just look at the code for an AI model, or must we examine the data and training process as well? - How do AI governance, risk, bias, explainability, MLOps, and incident response connect to one another? - Where should I start to understand the concepts covered in AI auditing certification courses like AAIA from a practical perspective? This course was created specifically to resolve this sense of uncertainty. For about 20 years, I have gained experience in IT service planning, development, PM, collaboration platform operation, groupware construction, chatbot service planning, and security and audit-related tasks. I have firsthand experience in how systems are planned, developed, and operated in actual organizations, and how failures, changes, security, and user requirements are interconnected. Furthermore, I have synthesized the perspectives of IT auditing and AI auditing through CISA and AAIA study programs. In this course, rather than diving deep into complex AI technology through math or development, I focus on the core concepts that auditors and IT practitioners must understand. We will examine AI systems by breaking them down into the flow of data, models, operations, security, governance, risk, and audit procedures, and summarize what controls and checkpoints are required at each stage. Through this course, students will understand that AI auditing is not simply "evaluating AI," but rather the task of inspecting governance, risk, and control systems to ensure that AI is used safely and responsibly within an organization. This course is suitable for: - Those new to AI auditing. - Those in IT auditing or security who want to expand into the AI domain. - Those who want to organize AI governance and risk from a practical perspective. - Those who want to grasp the overall concepts before starting AI audit-related studies such as AAIA. Upon completing the course, you will be able to answer the following questions yourself: - What components make up an AI system? - What should an AI auditor check during the data, model, and operation stages? - Why are AI governance and Responsible AI important? - How are AI risk, bias, explainability, privacy, and security connected? - What perspectives and evidence should be included in an AI audit report? In the rapidly changing era of AI, the ability to manage and inspect technology to make it trustworthy is just as important as the ability to use it well. This course is an introductory program for those who want to understand the big picture of AI auditing step-by-step from the beginning. Let's build the first standard for looking at IT and AI from an auditing perspective together.

This is a practical course for Linux beginners who struggle with saving, exiting, switching input modes, navigating, deleting, and copying/pasting because they are unfamiliar with vi/vim. Based on over 30 years of experience using Linux, this course is designed to help you step-by-step master the vi/vim basics and practical editing commands required for server tasks in a Rocky Linux 9 environment.

In the era of smart factories and autonomous driving, is our production line truly safe? The remarkable advancement of Artificial Intelligence (AI) has brought innovative productivity and efficiency to the automotive manufacturing industry, but it is simultaneously creating unprecedented security threats to the Operational Technology (OT) environment within factories. This lecture breaks down "OT Security"—which can often feel vague and difficult—in a clear and easy-to-understand manner through vivid, real-world examples from the automotive industry.

Master Claude Code from the basics to a professional level. Learn core features (CLAUDE.md, sub-agents, MCP, Hooks, etc.) to develop and deploy actual services, concluding with basic appendices for non-majors and advanced application lectures.

AI Tech DNA Series: Core Principles of Computer Basics from an AI Perspective is an introductory course designed to help you easily understand the fundamental computer concepts necessary for the AI era. By explaining basic principles such as CPU, memory, storage, networks, and data structures through real-life analogies and an AI-focused lens, it builds the solid foundational strength needed to advance into Python, AI, security, and the cloud.

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 is a 'Practical Linux Troubleshooting Course' where you analyze and solve problems together with generative AI, based on a Docker practice environment that reproduces 5 representative failures that occur in actual Linux operating environments. Even those who were overwhelmed about where to start examining problems can learn the problem-solving approach and thought process of field engineers through AI guidance.

In an era where AI writes code for us, the value of a "true architect" who can see through and control the macroscopic framework of a system becomes overwhelmingly higher. This course digs into the essence of low-level networks and TCP/UDP sockets hidden behind frameworks, cultivating the ability to design robust core engines that never crash even in the face of millions of traffic hits and large-scale data. Go beyond being a coder who blindly repeats copy-pasting, and leap forward to become an irreplaceable master who directs and controls AI with clear, system-level solutions.

AI is no longer a choice, but a matter of survival. Shorten development tasks that used to take 3 days down to 30 minutes; leave repetitive tasks to AI and focus on solving more important problems. Through AI-native development methods that are practical rather than theoretical, we will show you the definitive way to be recognized as an "AI-savvy developer" at your company.

An era where even IT beginners can become the 'CEO of their own platform' with just an idea, utilizing AI and Gnuboard! We will demonstrate the actual development process in detail, from planning to deployment, and even share various monetization methods such as advertising and shopping malls. Start your online business right now!

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 does not simply list concepts. 👉 It explains the entire flow of IT systems based on "how a service actually operates." User Request → Server Processing → Data Storage → Result Return Web/App → API → DB → Cloud 👉 Centered around this flow, it connects where, why, and how each technology is used.

This is a practical project course where you will build a complete web service from planning to deployment using AI coding tools. You will gain hands-on experience with the entire process—including database design, file storage implementation, and service operation—within a Windows environment to acquire practical development skills 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.

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 course explains IT terminology and system structures frequently used in the workplace in a way that even non-majors can understand at once. It is designed to help you understand the flow of corporate IT structures—from servers and databases to APIs, security, and the cloud—rather than just learning individual terms. We will help you build foundational IT skills that are immediately applicable to your work, so you will no longer be stuck due to technical jargon in IT meetings and tasks.

This is a process for completing IoT products without complex coding, using the Vibe Coding methodology powered by AI agents. You can experience the entire product development cycle in a condensed format—from embedded hardware control and AI vision recognition to PCB design, 3D printing, and web/app service development—allowing you to launch functional, commercial-grade IoT devices.

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.