Why AI Agents Fail: Practical Implementation Strategies for Understanding Data, Security, Cost, and Operational Hurdles

[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.

As the digital transformation of the manufacturing industry accelerates, production facilities, control systems, and industrial networks are becoming increasingly connected to external systems. Along with this, the possibility of cyberattacks leading to production shutdowns, quality degradation, technology leaks, and safety accidents is also growing. The [OT (Manufacturing) Security] Master Class for 4 Major Manufacturing Industries is a course that examines OT security threats that can occur in the automotive, semiconductor, chemical, and food/pharmaceutical industries, focusing on real-world manufacturing site cases. Participants will understand how production processes and facility environments differ across each industry and systematically learn about key security threats, causes of accidents, and response strategies specific to each sector. The course covers a wide range of topics in a single program, including smart factory and supply chain security in the automotive industry, protection of core processes and technical information in the semiconductor industry, control systems and safety accident response in the chemical industry, and quality, hygiene, and GMP data protection in the food and pharmaceutical industries. Rather than simply listing complex technologies or attack techniques, the course explains "what problems can occur," "why they occur," and "how to respond on-site" in a way that is easy for even beginners to understand. Through this lecture, you can compare the characteristics of the four major manufacturing industries and the differences in OT security, and learn the basic direction of security inspections and accident response required at manufacturing sites.

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.

This course examines major security threats and incident cases that can occur in the process control environment of the chemical industry, providing an easy-to-understand approach to AI-based anomaly detection and response. Participants will learn practical OT security, focusing on risks unique to the chemical industry such as production shutdowns, manipulation of process values, and hazardous substance leaks.

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.

"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.

"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.

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.

If you only know LangChain, it's just a chatbot; but if you know LangGraph and Multi-Agent patterns, it becomes a service. An active AI instructor will share the know-how to build operational AI Agent workflows from start to finish—going beyond simple prompt calls to handling tools, maintaining memory, and incorporating human-in-the-loop verification—using 17 practice notebooks and 4 multi-agent patterns (Subagents, Handoffs, Router, and Skills).

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

AI writes on Slack and Notion for me? Work smarter with MCP, which goes beyond the limits of existing AI!

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.

This course is not about non-developer office workers learning coding itself, but rather an education focused on developing the ability to solve business problems directly using AI agents. Previously, one had to rely on IT departments or outsourced development when problems arose, but we are now in an era where you can design alongside AI and create immediate prototypes to implement task automation. The core competencies required for this are problem definition, establishing solution strategies through AI collaboration, and the ability to build the necessary tools yourself. In particular, by utilizing Codex CLI, existing ChatGPT users can practice agentic coding immediately without additional costs, allowing non-developers to quickly gain practical experience. The curriculum is structured step-by-step, covering everything from understanding changes in the AI agent era to development basics, terminal usage, Codex CLI-based agentic coding, problem structuring, Django web app development, and the creation of actual task automation apps. Learners can secure task automation capabilities by directly building applications applicable to real-world work, such as To-Do lists, checklists, schedule management, meeting minutes, and summarization tools. The entire course is designed as a modular micro-learning system composed of short units, allowing for rapid learning of necessary content and immediate reuse during work.

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

Work automation has always been the domain of developers, but with Cowork, you can create your own office-specialized workflows just by making requests in Korean within a chat window, without any coding knowledge. In this course, we will cover from scratch how to maximize office work efficiency through no-code automation.

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 Kiwoom Securities API-based automated stock trading system from scratch using the core features of Claude Code (MCP, Agents, Skills). It's perfectly fine for beginners. Get started with Claude Code right now!

This is an advanced course focused on designing and implementing Multi-LLM architectures and orchestration-centered Agent systems (Main/Sub, Tool, Task Runtime, Agent Registry) by strategically combining GPT, Gemini, and LLaMA (local) based on Spring AI and Spring Boot. Moving beyond simple LLM calls, the curriculum covers the implementation of scalable, stable, and continuously improving AI systems. This involves applying Agentic Workflow Patterns (Chain, Parallel, Routing, Orchestrator–Workers, Evaluator–Optimizer) and Multi-Agent structures, separating execution layers like RAG and external APIs/DBs via Tool/ToolRegistry, and utilizing DAG engines, YAML declarative workflows, and Validated DSL (validation immediately after loading). Furthermore, the course includes Circuit Breakers, Reactive Streams, Redis monitoring, parallel processing, and iterative evaluation loops. It expands from Thymeleaf (SSR) exercises to decoupled Front-end/Back-end architectures using React and REST, while integrating tool and agent runtimes via MCP (Model Context Protocol) to build AI architecture design capabilities at a production-ready level. The ultimate goal is to evolve beyond being a simple AI user who merely integrates APIs and writes prompts, becoming a developer capable of designing AI systems—explaining and balancing Multi-LLM, agents, workflows, declarations, and validation within a single execution architecture.

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.

[Up-to-Date Knowledge for Current Times] 1. Changes brought by AX, ChatGPT, and robot technology. 2. Commonalities of Blockbuster-Kodak Film-Nokia. 3. Five Current AX Keywords. - OOOO coin to maintain dollar hegemony. - Musk's OOOO to cut government operating costs. - Trump's OOOO strategic reserve. - China's OO kindergarten, OO receiving private education. - China's OO factory, with no workers, OO is no longer needed. 4. ChatGPT/Gemini/Grok - Write prompts based on previously learned content and compare results - Generate images with Claymotion infographics

If you want to create your own AI service without coding, this course is the perfect solution. Using the Dify no-code platform, you can create high-quality AI apps with just your ideas. Instead of complex theory, it's structured around hands-on projects, allowing both AI beginners and working professionals to develop practical skills.

The topic is no-code data analysis utilizing generative AI tools. We perform all stages of data analysis, including data collection, analysis, visualization, and report writing, using AI tools such as ChatGPT, Gemini, Claude, Perplexity, and Julius.

You can automate repetitive and tedious tasks using GPTs. Even non-developers can automate more complex tasks with GPTs by linking various external automation services!

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"! 😊

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

Are you confused about which technology trends really matter among the flood of information? We've analyzed global reports from Gartner, Microsoft, and others to clearly explain 10 key technologies (multi-agent systems, physical AI, AI security, etc.) that will define 2026.

: "From Mathematical Foundations to the Latest Models, Completing the Deep Learning Pipeline with PyTorch (44 Lectures in Total)" The era of simply learning how to call model.fit() is over. From the very basics of artificial neural networks—differentiation and gradient descent—to essential PyTorch techniques used in the industry, and CNN/RNN for handling image and time-series data! We will help you systematically master the entire process of deep learning. Go beyond analyzed data and step into the amazing world of deep learning, where artificial intelligence mimicking the human brain learns and makes decisions on its own.