[OT Security - ③ Chemical Industry] Understanding Manufacturing Security in the AI Era: Focusing on Field Case Studies

"Throw away the cliché AI theories and chatbot examples scattered all over YouTube. This is Korea's one and only '7 Major Industry Integrated Manufacturing AI Bible' that understands the language of manufacturing and pierces through the essence of the process." Hello, I am Byte Detective, your knowledge sharer. Currently, countless companies and practitioners are calling for 'Manufacturing DX (Digital Transformation)' and 'AI Adoption.' However, the majority of courses on the market are limited to vague theories from IT developers or consultants who have no understanding of the harsh practical realities of the manufacturing field. This course is not a lecture for the sake of theory. By organically combining the actual domain knowledge of Korea's top 7 representative manufacturing industries with the latest AI frameworks, it provides a 'Practical Manufacturing DX Scenario Architecture' that can be applied to the field starting tomorrow.

The semiconductor industry is a representative manufacturing sector where production facilities, control systems, partners, and data are closely interconnected. For this reason, even a small security incident or system failure can lead to production shutdowns, quality issues, delivery delays, and technology leaks. This lecture explains the OT security threats that can occur at semiconductor manufacturing sites in a way that even beginners can easily understand. Rather than focusing on complex technical explanations, it centers on what security problems can arise in the actual field, why the semiconductor industry is a target for attacks, and how security incidents impact companies. Furthermore, it examines how security threats are evolving as manufacturing environments become more intelligent with the spread of AI and smart factories.

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.

[Introduction to Security Incident Response: Learning through Scenarios of Web Server Hacking, Ransomware, and Account Takeover] This course examines why various information security incidents—such as web server hacking, ransomware, account takeover, and internal penetration—occur and how they spread, categorized by incident type. Students will follow each incident scenario to understand the attack flow, analyze the core causes of the incident, and learn how to resolve issues and prevent recurrence through security architectures such as firewalls, DMZ, access control, privilege management, backup, and log monitoring. Rather than a simple explanation of security concepts, this is a scenario-based introduction to information security that provides a comprehensive understanding from root cause analysis to resolution strategies.

"Understanding Manufacturing Security in the AI Era through Field Cases" is a course designed to provide an easy understanding of OT security, which is growing in importance within smart factories and AI-based manufacturing environments, focusing on real-world field cases. This lecture explains core concepts frequently encountered in manufacturing sites, such as OT, ICS, PLC, SCADA, HMI, and MES, and compares the differences between IT security and OT security. Furthermore, it examines security threats that can occur on the manufacturing floor—such as ransomware, remote access exploitation, partner account hijacking, production line shutdowns, equipment malfunctions, and data forgery—through case studies. Through this course, students will understand the basic structure of OT security in manufacturing and identify the security perspectives necessary to protect production facilities and industrial control systems. Additionally, it provides a common foundation for further learning in industry-specific manufacturing security courses.

Beyond the era of simply using AI, we are now in an era that requires people who can design AI. This course is a master roadmap that systematically organizes the entire design map of AI agents, from "Introduction → Structure → Design → Operation." Based on RAG, Tool Calling, Memory, and Multi-Agent structures, you will learn how to design and scale AI agents from an architect's perspective. If you want to grow into someone who designs AI systems rather than just someone who "uses" AI, this course will provide the direction.

This course is a specialized program that covers practical application strategies for utilizing artificial intelligence (AI) in the construction and civil engineering fields. In the construction industry where digital transformation is accelerating, AI is driving innovation across design, construction, safety, and quality management. This course focuses on learning practical application cases that can be utilized in actual field sites, including smart construction, digital twins, AI-based equipment control, safety monitoring, and quality verification.

The shipbuilding and maritime industry is a representative field of traditional heavy industry, but it is securing new competitiveness through the combination of digital transformation and artificial intelligence (AI) technology. This course is structured around specific application cases actually used in the field, such as AI-based shipyard production management, ship design automation, maritime logistics optimization, and predictive maintenance system construction. With a field-centered approach, you can understand not just simple theory but **'how AI actually works in shipyards'**. Additionally, it covers data infrastructure construction, model training, and constraints specific to the marine environment that must be considered during the AI technology implementation phase.

"Smart Factory—it sounds cool, but can't quite picture it in your head?" The news talks about the 4th Industrial Revolution and AI factories every day, but when you actually look for information, it's full of "alien languages" like PLC, MES, ERP, and Edge Computing. What non-majors need isn't a complex circuit diagram, but a 'map' that shows how the whole system works. This course strips away difficult engineering jargon and explains everything about smart factories through intuitive illustrations and analogies that anyone can understand.

"The Fourth Industrial Revolution, AI factories... The terms are familiar, but can't you visualize the structure?" Smart Factory, often called the future of manufacturing. While related articles pour out and it appears as a required competency in job postings, the barrier feels far too high for non-majors. "Did you give up because of abbreviations that sound like alien languages, such as PLC, MES, or ERP?" "Are you afraid to even start because you lack knowledge in coding or engineering?" Don't worry. This lecture deals with 'structure,' not 'engineering.' Instead of complex text, we will help you complete a full map of the smart factory in your head using intuitive drawings and diagrams, just like assembling Lego blocks.

This course covers practical strategies for leveraging AI in the machinery and metal processing industry to enhance productivity and quality. It analyzes key process data from CNC, welding, cutting, and other operations, explaining how AI technology is applied to reduce defect rates, enable predictive maintenance, and manage worker safety through real-world case studies. Learners will understand AI-based processing optimization methods that can be immediately implemented in the field, from small and medium enterprises to large corporations, and gain insights to realize manufacturing innovation in global competition.

This course covers how to leverage AI in the food and pharmaceutical manufacturing industry to enhance productivity and quality. Through real-world case studies, you'll learn how AI is applied in key stages such as raw material management, production processes, quality inspection, and regulatory compliance, while understanding defect rate reduction and efficient operational strategies. Through this course, learners will master ▲characteristics of the food and pharmaceutical industry and the necessity of AI adoption ▲data-driven quality management ▲predictive maintenance and equipment optimization ▲regulatory compliance monitoring and risk management ▲analysis of domestic and international implementation cases, gaining strategies and insights that can be immediately applied in the field.

The chemical and fine chemical manufacturing industry is a sector that requires complex processes and high safety standards. This course covers strategies for leveraging AI to increase productivity, reduce costs, and enhance safety. You can systematically learn practical skills centered on AI application cases that can be immediately applied in actual field settings, including process data analysis, quality prediction, equipment predictive maintenance, and environmental regulation compliance.

The electronics and semiconductor industry is a field where data-driven management and innovation are particularly crucial due to ultra-precision processes and complex supply chains. This course covers practical strategies that can be directly applied in electronics and semiconductor manufacturing, including defect detection, process optimization, predictive maintenance, and supply chain management using AI technology. Along with real-world cases from global companies, the course also presents low-cost, high-efficiency AI implementation methods that small and medium-sized enterprises can realistically utilize. Through this, students will be able to understand and apply AI-based manufacturing strategies that not only improve productivity and reduce costs, but also build future competitiveness.

The automotive and parts manufacturing industry is a field where innovation is essential amid fierce global competition and complex supply chains. This course focuses on how AI technology can be applied in the field, explaining actual cases including production efficiency improvement, quality inspection automation, equipment predictive maintenance, and supply chain optimization. From the foundational understanding needed for AI implementation to strategies and risk management considerations for field application, this course covers topics step by step, providing knowledge and insights that practitioners and managers can immediately utilize.

Digital transformation (DX) is not a choice but a necessity. This course serves as the first step in digital transformation for all employees, providing easy and clear explanations from core DX concepts to business innovation cases. Don't fall behind in this changing era—develop the power to grow yourself and lead organizational innovation! Please don't overthink this lecture and take it with a light heart.

The Key to Unlocking the Value of Ideas: Intellectual Property Ability Test (IPAT) Core Lecture This course goes beyond simply passing an exam; it is a process of learning practical methods to protect invisible 'ideas,' create value, and further transform them into powerful 'assets.' We help you eliminate the vagueness surrounding Intellectual Property (IP) and grow into a competitive expert in any field. Have you been hesitating to even start studying because of the massive official textbook? This course does not cover every single detail of the official National Certified Intellectual Property Ability Test (IPAT) textbook. Instead, it is structured by selecting only the core concepts and high-scoring points that frequently appear on the exam. Exam preparation is not necessarily better just because it's long. The secret to passing is learning only what is necessary, accurately, and repeatedly. Discover that secret in this lecture.

**"Digital Forensic Techniques by Byte Detective: Evidence Collection and Securing"** is a course focused on how to collect and preserve digital evidence required in cases of cybercrime, internal information leakage, and security incidents. From the basic concepts of digital forensics to the principles of evidence collection, maintaining integrity, and legal procedures for securing evidence, this course explains everything through case studies and procedural steps so that even beginners can understand. You can systematically learn the forensic mindset and core concepts of securing evidence that are essential to know before using professional analysis tools.

Incident response is less about mastering tools and more about knowing what to judge first. Rather than focusing on how to analyze malware, this course explains the realistic thought process of determining **"whether the current situation is an actual incident and what actions to take first."** Using webtoon-based real-world scenarios, we have organized the entire flow of incident response—from identifying signs of intrusion to incident assessment, initial response, containment, and analysis/forensics—in a way that even non-experts can understand. This is not just a collection of fragmented technical explanations; it is a course where you learn the decision-making criteria and response perspectives that practitioners can apply immediately in the field.

This is an introductory information security course that breaks down complex cyberattack techniques as easily and engagingly as a movie. From traditional hacking methods to attack techniques occurring in the latest cloud environments, everything is organized for easy understanding based on real-world cases and scenarios. Even if you don't know technical terms, anyone can follow along through the active use of analogies, visual aids, and storytelling, structured so that vague security concepts remain clearly in your mind. "This course is designed for those who only had a vague knowledge of security to understand everything at once—from the principles and flow of hacking to actual attack methods and response strategies."

The semiconductor industry is a representative manufacturing sector where production facilities, control systems, partners, and data are closely interconnected. For this reason, even a small security incident or system failure can lead to production shutdowns, quality issues, delivery delays, and technology leaks. This lecture explains the OT security threats that can occur at semiconductor manufacturing sites in a way that even beginners can easily understand. Rather than focusing on complex technical explanations, it centers on what security problems can arise in the actual field, why the semiconductor industry is a target for attacks, and how security incidents impact companies. Furthermore, it examines how security threats are evolving as manufacturing environments become more intelligent with the spread of AI and smart factories.

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.

"Understanding Manufacturing Security in the AI Era through Field Cases" is a course designed to provide an easy understanding of OT security, which is growing in importance within smart factories and AI-based manufacturing environments, focusing on real-world field cases. This lecture explains core concepts frequently encountered in manufacturing sites, such as OT, ICS, PLC, SCADA, HMI, and MES, and compares the differences between IT security and OT security. Furthermore, it examines security threats that can occur on the manufacturing floor—such as ransomware, remote access exploitation, partner account hijacking, production line shutdowns, equipment malfunctions, and data forgery—through case studies. Through this course, students will understand the basic structure of OT security in manufacturing and identify the security perspectives necessary to protect production facilities and industrial control systems. Additionally, it provides a common foundation for further learning in industry-specific manufacturing security courses.

Generative AI is rewriting how the world works — and the people who learn it now will lead the next decade. Every industry is being reshaped in real time. Marketers are creating campaigns in minutes. Developers are shipping code faster than ever. Entire teams are automating work that used to take days. And at the center of it all sits one skill that separates those who get left behind from those who get ahead: knowing how to actually use Generative AI. The problem? Most people are still only scratching the surface. They've typed a question into ChatGPT, gotten an average answer, and assumed that's all there is. But beneath that simple chat box is one of the most powerful technologies ever built — and once you understand how it works and how to direct it, you'll never work the same way again. That's exactly what this course is built to do. Introduction to Generative AI takes you from complete beginner to confident, capable AI user — no coding, no maths, and no prior experience required. In clear, jargon-free language, you'll discover what Generative AI really is, how it works under the hood, and how to put it to work in your job, your business, and your everyday life. This isn't a dry, theoretical lecture series. It's a practical, demo-driven journey packed with real examples you can follow and copy immediately. You'll start with the foundations — what Artificial Intelligence, Machine Learning, and Deep Learning actually mean, and how Generative AI fits into the bigger picture. You'll explore ChatGPT's features and capabilities hands-on, understand why this technology has exploded so quickly, and trace its remarkable evolution. From there, you'll demystify the engine that powers it all: Large Language Models. You'll see exactly how next-word prediction, embeddings, and fine-tuning work, and you'll understand game-changing concepts like Retrieval Augmented Generation (RAG) and the rise of Agentic AI — the difference between an assistant that answers and one that acts. Then comes the real superpower: prompt engineering. This is where most learners go from "AI is interesting" to "AI is indispensable." You won't just learn what prompting is — you'll master more than a dozen proven techniques used by professionals every day, including chain-of-thought prompting, zero/one/few-shot prompting, tabular prompting, perspective prompting, comparative prompting, reverse prompting, the RGC framework, and many more. You'll get ready-to-use prompt starters, learn how to revise and sharpen your prompts for dramatically better results, and discover how to generate fresh ideas, marketing copy, client emails, and content at scale. By the end, you'll know how to make AI do precisely what you want — consistently. You'll see it all in action. This course is loaded with practical demonstrations across real business scenarios. Watch AI summarise meetings and capture insights with an AI notetaker, draft polished email responses in seconds, and spin up multiple marketing headline variations from a single product image. You'll explore how Generative AI is transforming software development, retail, and marketing, and you'll see real tools at work — generating working code with GitHub Copilot and creating images and video with cutting-edge tools like Amazon Nova. These aren't hypotheticals. They're workflows you can start using the moment you finish the lesson. But great power demands responsibility — and this course doesn't skip the hard parts. You'll dive into Responsible AI and learn how to spot and manage hallucinations, factual inaccuracies, bias, and fairness issues. You'll understand the genuine technical limitations of today's models and the practical workarounds that experienced users rely on. Through real examples — including safety refusals and bias-correction rewrites — you'll learn to use these tools wisely, ethically, and with confidence, the way professionals and organisations are expected to. And you'll finish looking forward, not just at today. You'll discover how Generative AI is disrupting search and reshaping the way the world finds information, explore the road toward Artificial General Intelligence (AGI), and get a clear-eyed view of the jobs, certifications, and fast-growing career opportunities this field is creating. Whether you want to future-proof your career, boost your productivity, or build something new, you'll leave knowing exactly where this technology is heading and how to ride the wave. Why learn from this course? You'll be joining a community of over 207,000+ students taught across leading platforms, backed by a 4.6 instructor rating and 13,000+ reviews. Every concept is explained simply, every technique is shown in practice, and every lesson is designed to take you one step closer to genuine confidence with AI. No fluff. No overwhelm. Just clear, practical, up-to-date learning that respects your time. This course is for you if you're a beginner curious about AI, a professional who wants to work faster and smarter, a marketer, creator, developer, entrepreneur, or simply someone who refuses to be left behind by the biggest technology shift of our generation. If you can use a web browser, you can do this course — and you can start today. The gap between people who use AI and people who master it is widening every single day. The tools are here. The opportunity is now. The only question is which side of that gap you want to be on. Enrol today and start your journey from AI curious to AI confident — one practical, powerful lesson at a time.

With the advancement of generative AI, many companies are pursuing AX (AI Transformation). However, in the actual field, there are not many educational programs that systematically teach what to do and how to do it compared to the demand that "AX must be done." While most AI education focuses on how to use generative AI or write prompts, this course focuses on the "AX Strategy Planning Methodology" for transforming corporate tasks and services into AI-based ones. This course is based on the practical experience of a 25-year expert who has performed DX/AX consulting and training for large corporations, the financial sector, public institutions, and various companies in the actual IT field. It allows you to learn from a practical perspective not just how to use AI well, but which tasks should undergo AX, to what extent AI should make decisions, how to control risks, and how to design and verify AX projects. Furthermore, it systematically covers core content necessary for actual AX implementation, from understanding the essence of AX to AI thinking systems, AX design methodology, Human-AI role separation, Guardrail design, and KPI and verification structures. In particular, it goes beyond simple theoretical education. Based on real corporate cases such as insurance underwriting, customer consultation, manufacturing quality, internal work support, marketing recommendations, development productivity, and management decision-making, it provides guide templates and sample materials for AX problem definitions, AX hypothesis definitions, AX performance designs, AX service structure diagrams, Guardrail designs, and AX verification plans. This ensures that after taking the course, you can secure the practical capabilities to easily plan and promote actual AX tasks. The biggest differentiator of this lecture is that it teaches how to plan and design AX from the perspective of someone who actually performs AX projects. Specifically, by providing AX strategy planning output templates and seven industry-specific AX cases that can be used in the field, it is designed so that students can refer to cases most similar to their own work and apply them immediately by modifying them to fit their environment. In short, this is not a course to create AI users, but a process to create AX strategy planners who can design and execute a company's AX.

No coding knowledge required, build your very first service with Google Stitch An all-in-one AI development workflow that connects everything from planning to deployment in a single stream

You can transform your ideas into beautiful presentations in just a few minutes. No more spending hours struggling with slide design. With GAMMA's AI technology, you can dramatically improve your content creation process.

The recent Coupang personal information leak has been recorded as the largest data breach in South Korea's history, marking an instance where the personal information of virtually every South Korean citizen was compromised. However, the debate regarding the effectiveness of ISMS-P concluded with meaningless improvement measures such as mock hacking and certification revocation. As of December 11, 2025, companies like Coupang—which were subjects of the Personal Information Processing Policy Evaluation System conducted by the Personal Information Protection Commission in 2024—continue to operate in violation of more than 10 criteria of that evaluation system. The reason for this lies in human error involving Coupang's personal information team (comprised of top domestic and international experts) and ISMS-P auditors (who hold the highest domestic and international qualifications). With basic common knowledge of the Personal Information Protection Act, this recent leak, as well as breaches at Gmarket, Netmarble, SKT, KT, and LG U+, could have all been prevented. In reality, accidents continue to occur because customers' personal information is not protected—or appropriate protective measures are not established and operated—due to human issues such as inadequate preliminary inspections and differences in legal interpretation. Through this lecture, you can acquire the skills to evaluate personal information transparently and objectively, with the hope that personal information protection for customers will be achieved through professional training aimed at proper inspection methods and eliminating blind spots.

An introductory AI lecture tailored for those new to artificial intelligence! It easily summarizes core concepts from data to generative AI. The goal is not to build AI, but to achieve a level of practical understanding where you can ask the right questions and explain the technology.

For those of you who have completed intermediate SwiftUI, it is now time to integrate AI into your apps. Complete an on-device AI app that runs locally without an internet connection using Apple Intelligence and the FoundationModels framework.

The shortage of PMs in security consulting firms is a persistent issue. Consequently, there are many cases where individuals in their 40s and 50s from completely different fields have been entering the industry to handle PM duties and client communications. Since these PMs in their 40s and 50s lack experience in technical areas, consulting, and security, they find the work very challenging. They often join with the mindset of learning through handovers from other PMs. I have also been providing training and handovers to these PMs based on the following content, and the satisfaction levels have been high.

You can easily understand the principles and attack methods of **SQL Injection (SQLi)**, the most frequent and dangerous web vulnerability.

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!

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.

Based on over 100 deep learning training sessions, this course systematically organizes the core foundational theories that students found most challenging. The course connects mathematical intuition, model learning principles, and code implementation step by step in a way that even non-majors can understand, deeply covering the fundamental structure and operating principles of how AI models learn, rather than just library usage. This is a practical introductory course designed to help you grow into a skilled engineer who understands AI principles by implementing core deep learning foundational technologies such as gradient descent, loss functions, optimization, perceptrons, multilayer neural networks, and backpropagation through both formulas and code.

AI, the Key to Opening the World of Statistics "AI, by enabling easy mastery of complex statistical principles and analysis techniques, uncovers hidden meanings in data and provides insights for better decision-making. AI is now beyond a complex statistical calculator; it is a companion supporting statistical thinking."

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.

Customer analysis completed with Excel and Orange, from cross-selling to A/B testing and churn risk management all at once

"The deep learning code runs, but why do the formulas in papers look so unfamiliar?" As you study AI, you eventually hit a wall of mathematical formulas. If you trace the source of that wall, it usually leads back to not having a solid foundation in the most basic mathematical language. Starting with the language of sets, this course covers core concepts across 18 lectures, including equations, functions, sequences, exponents/logarithms, and trigonometric functions. We don't make you memorize formulas. While we briefly touch upon how these connect to the context of AI, the primary goal of this course is one thing — to build an unshakable foundation for when you later learn linear algebra, calculus, and probability/statistics. As the first part of the Suminjeongeum series, this course will provide you with the common language needed to properly digest the remaining three parts.

"The Fourth Industrial Revolution, AI factories... The terms are familiar, but can't you visualize the structure?" Smart Factory, often called the future of manufacturing. While related articles pour out and it appears as a required competency in job postings, the barrier feels far too high for non-majors. "Did you give up because of abbreviations that sound like alien languages, such as PLC, MES, or ERP?" "Are you afraid to even start because you lack knowledge in coding or engineering?" Don't worry. This lecture deals with 'structure,' not 'engineering.' Instead of complex text, we will help you complete a full map of the smart factory in your head using intuitive drawings and diagrams, just like assembling Lego blocks.