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.

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.

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.

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 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 Awakening the Value of Ideas: Intellectual Property Ability Test (IPAT) Core Lecture This course goes beyond simply passing the exam—it's a process of learning practical methods to protect invisible 'ideas,' create value, and ultimately transform them into powerful 'assets.' It eliminates vague notions about intellectual property (IP) and helps you grow into a competitive expert in any field. Have you hesitated to even start studying because of the extensive official textbook? This course does not cover all content from 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. Longer exam preparation is not necessarily better. The secret to passing is learning only what's necessary, accurately, and through repetition. Discover that secret in this lecture.

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 course is an introductory information security lecture that breaks down complex cyber attack techniques in an easy and engaging way, like a movie. From traditional hacking methods to the latest attack techniques in cloud environments, everything is organized in an easy-to-understand manner based on real cases and scenarios. Even if you don't know technical terms, anyone can follow along as we actively use analogies, visual materials, and storytelling, and it's structured so that vague security concepts clearly stick in your mind. "This course is designed for those who only had a vague understanding of security to comprehend everything at once: 'hacking principles and flow → actual attack methods → response strategies.'"

When studying information security, you've probably had this thought at least once: "Firewall, CSPM, SIEM... I've heard the names, but I'm not exactly sure what they do." This course is designed for those new to information security to clearly grasp the concepts of the 'security solution landscape.' From each solution's concepts, key functions, pros and cons, case studies, to the latest trends... With a total of 23 lectures, how about clearing up the vagueness about security solutions right now?

"Vulnerability Analysis Techniques Revealed by the Byte Detective: Practical Understanding and Diagnostic Strategies" covers the process that goes beyond security basics to connect vulnerability discovery → analysis → diagnostic strategy development in real-world environments. This course breaks down difficult security concepts in an easy-to-understand way for beginners, and is structured with procedure-focused, example-driven, and case-based explanations that can be immediately applied in practice. This course will help security personnel, IT practitioners, and those preparing for careers in the security field develop core principles of vulnerability analysis and practical expertise.

"Prepare for the future talent who will lead the AI era, right now!" Artificial intelligence (AI) has now become a core technology that brings innovation to our lives and industries. As various companies and institutions actively adopt AI technology, the demand for related jobs is rapidly increasing, which is also a great opportunity in the job market. However, many people feel at a loss about what and how to prepare to enter the AI field. The "AI Job Roadmap" e-learning course provides systematic and practical job strategies for job seekers, career changers, and non-majors who want to enter the AI field. It summarizes everything about the AI field, from basic concepts to practical projects and job preparation. Through this course, you can build a solid technical capacity in the AI field and complete your own powerful portfolio to grow into a key talent needed in the AI industry.

**"AI Philosophy - Ethics and Challenges in the Age of Artificial Intelligence"** is a topic that deals with the ethical and philosophical exploration of the development of artificial intelligence (AI) and its impact on human society and culture. This topic goes beyond simple technological development and delves into how AI affects human life and what ethical decisions we should make accordingly.

As AI technology rapidly advances, the nature of existing jobs is changing and new opportunities are being created. Accordingly, not only technology-centered jobs such as data analysts, AI engineers, and cloud architects, but also hybrid jobs such as AI ethics experts, digital twin designers, and sentiment data analysts are attracting attention. In addition, creative job groups that utilize technology, such as EdTech experts, digital healthcare consultants, and virtual reality creators, are also emerging. As AI becomes a tool that assists and expands human work, talent with continuous learning ability and creative thinking will become a key factor in achieving success.

The National Certified SMAT (Service Management Ability Test) is administered by the Korea Productivity Center (KPC) and is a nationally certified private qualification aimed at fostering key talent in the service industry. Beyond mere theoretical assessment, it focuses on verifying practical competencies to cope with and manage various situations that arise in real service environments. This lecture provides a core summary of topics that are genuinely important and frequently appear in exams.

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.

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 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.

This is a lecture that studies Vision Transformer, one of the latest deep learning technologies, and implements a paper using Pytorch. Come experience the new future of the vision field with me!

This course is designed to teach the entire process of 'AI Training Data Construction,' which is essential for successfully executing AI modeling projects. Learners will not simply remain at the theoretical knowledge level, but will experience step-by-step the data construction processes required in actual practice. Specifically, the course covers the entire process from AI training data planning → acquisition → storage → preprocessing → labeling → pseudonymization and transformation through hands-on practice, structured to develop practical skills that can be immediately applied in the field. Additionally, learners will systematically study the most important data management capabilities in AI projects, such as data quality management and security issues, personal information de-identification processing, and dataset optimization. Through this, learners can grow from simple data collectors into data specialists who can proactively plan and execute AI projects. 👉 Through this course, learners will understand how to construct high-quality training data that determines AI model performance and acquire practical capabilities to effectively apply this in real work environments.

🚀 Practical AI Anomaly Detection with Databricks! 💡 Stop using expensive and slow models! From large-scale data optimization to real-time deployment, complete an anomaly detection AI that can be used immediately in corporate practice.

Claude AI First Steps: Get It Right from the Start, Directly Applicable in Practice! Want to use it smarter? Start with Claude AI.

It's now an era where data speaks, not intuition. Learn data analysis easily with ChatGPT!

Understand the basic concepts and latest trends of big data, and through technical understanding of big data analysis techniques, extract data patterns to present methods for business application. Through big data, you can create new businesses and develop insights into future business environments.

Learn how to use OpenCV and process images through a practical implementation of business card recognition. OpenCV is briefly explained, and the OpenCV functions required to implement business card recognition are explained in more detail. In other words, rather than a basic course, it provides an essence for the practical application of business card recognition. It also includes a method of utilizing Tesseract and Microsoft's OCR engine. The source code of this lecture is based on Python, but since you will learn the OpenCV classes and functions used and the image recognition and processing technology, it will not be difficult to apply it to Android and iOS based on this. Those who take the course will be provided with lecture slides and actual business card recognition source code. The lecture contents were further improved and verified through three offline seminars in January and February 2017, and the instructor has carefully recorded them again for online use. These are the OpenCV functions used in this lecture. cv2.Canny() cv2.GaussianBlur() cv2.VideoCapture() cv2.adaptiveThreshold() cv2.approxPolyDP() cv2.arcLength() cv2.boundingRect() cv2.boxPoints() cv2.contourArea() cv2.convertScaleAbs() cv2.createTrackbar() cv2.cvtColor() cv2.destroyAllWindows() cv2.dilate() cv2.drawContour s() cv2.findContours() cv2.getAffineTransform() cv2.getPerspectiveTransform() cv2.getTrackbarPos() cv2.imread() cv2.imshow() cv2.imwrite() cv2.minAreaRect() cv2.namedWindow() cv2.rectangle() cv2.resize() cv2.threshold() cv2.waitKey() cv2.warpAffine() cv2.warpPerspective()

Have you ever regretted focusing only on notes instead of making eye contact, or failing to accurately record meeting details after an important client meeting? Don't worry anymore! In this lecture, we'll help you build your own CRM assistant using Vibe Coding to summarize key information with AI and neatly save meeting content. You'll learn how to drastically reduce cumbersome document creation time, maximize work productivity, and revolutionize customer management!

In the AX era where AI technology and UX design converge, what strategies should product teams use to design customer experiences? A 17-year veteran senior researcher from a major corporation and knowledge sharer with a PhD in HCI will share insights based on the latest trends, use cases, and research findings.

This course is designed to learn the fundamental theories and practical processes necessary for applying AI modeling and service planning to real-world work environments. Learners can acquire essential foundational knowledge to skillfully perform AI modeling projects and experience various practical procedures used in actual business settings. The course is specifically structured to provide step-by-step learning of the entire workflow from AI service environment analysis → goal setting → requirements analysis → service model design → scenario planning → utilization planning → execution plan development → performance evaluation planning. Through this approach, learners can develop systematic thinking and practical application skills for how to introduce and utilize AI from business and service planning perspectives, rather than limiting themselves to purely technical learning. Upon completing this course, learners will understand the overall planning and execution process of AI projects and will be able to strengthen their capabilities as AI service planners, PMs, and data-driven strategists in actual corporate environments.

We invite you to the fascinating world of coding where you analyze and visualize financial statements using only prompts. Without a single line of code, you create and deploy a service in consultation with AI.

If you want to be recognized as a machine learning expert based on large-scale data, from understanding the core framework of Spark machine learning, to SQL-based data processing through difficult practical problems, to data analysis through business domain analysis, and to the ability to implement optimized machine learning models, please join this course.

Learn context engineering techniques for creating high-quality AI agents through hands-on practice.

We will make the entire data analysis process more accessible using chatGPT and generative AI. While gaining a better understanding of the data analysis process, you can also learn how to apply AI in practical data science.

This is a course on creating blog images using DALL-E 3. This course provides practical knowledge and hands-on opportunities from the basics of image generation technology to advanced usage techniques and problem-solving strategies.