For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| BUS2011 | Marketing Research Methodology | 3 | 6 | Major | Bachelor | Business Administration | English | Yes | |
| The purpose of this course is to provide participants with the skills needed to conduct basic market research studies, work with research departments and/ or companies to obtain the information needed for decision making and to evaluate and interpret research results. The course covers issues of basic data collection and analysis. Methodologies for designing new products, segmenting markets and positioning products. As business managers in every field and at every level are called upon to make decisions on the basis of collected information, most participants will find this course relevant, regardless of their chosen fields of specialization. | |||||||||
| BUS3031 | Marketing Communication | 3 | 6 | Major | Bachelor | Business Administration | - | No | |
| This course covers important issues in the design and implementation of effective marketing communication programs, such as advertising and promotions. Specifically, the goals of this course are: 1) to enhance your understanding of the important issues involved in integrated marketing communication; 2) to expose you to relevant theories and models that can be useful for your understanding marketing communication; and 3) to provide you with a strategic perspective on managing effective marketing communication. | |||||||||
| CHS2003 | Robust System Design with Big Data Analytics and Artificial Intelligence | 2 | 4 | Major | Bachelor | 1-4 | Challenge Semester | Korean | Yes |
| In this course, the fundamental theories and methodologies on big-data analytics and artificial intelligence (AI) algorithms for prognostics and health management (PHM) of engineering systems are mainly covered. More specifically, the reliability analysis, sensor-based big-data collection, signal processing, statistical feature extraction and selection, and AI-based modeling are studied, and the hands-on practices are also carried out. In addition, various case examples are introduced to study the robust engineering system design using the big-data analytics and AI algorithms. | |||||||||
| CHS2017 | A new human, phono sapiens Experience Design | 3 | 6 | Major | Bachelor | 1-4 | Challenge Semester | - | No |
| As humans started using smartphones, they are experiencing changes in consumption psychology, consumer behavior, and market ecosystems due to rapidly changing lifestyles. This represents a new type of human, the main protagonist of the revolution, called Phono Sapiens. As consumption civilization changes, we learn about digital transformation and changes in business models driven by the development and evolution of big data, artificial intelligence, and digital platforms. We analyze and learn the direction of digital experience design (Digital Experience Design) based on digital transformation. Companies provide and understand the direction of new business innovation and change in accordance with rapidly changing trends for Phono Sapiens, the new consumers. | |||||||||
| CHS2018 | Storytelling that Builds Brands | 3 | 6 | Major | Bachelor | Challenge Semester | Korean | Yes | |
| Modern marketing has become increasingly digital, with the rise of data-driven performance marketing and programmatic advertising. Although these strategies concentrate on measuring and analyzing consumer actions- such as product downloads, purchases, and page visits- to enhance efficiency, they often overlook the core purpose of marketing and the foundations of consumer behavior. Marketing transcends merely driving actions; it entails comprehending the psychological and social factors that influence such behaviors and connecting with consumers on a deeper level. This is particularly applicable in traditional marketing campaigns and content marketing. This class delves into the significance of content, emphasizing storytelling in marketing. By examining various case studies, where stories established a brand's identity, revitalized a brand, or renewed a brand, transformed the organization, changed the culture of the organization, or elevated the brand, or navigated a crisis, achieved global reach, or created a new category, and strengthened customer loyalty or enhanced social impact, we will evaluate the successes and failures of brands leveraging narrative techniques, providing students with a comprehensive understanding of brand marketing strategies. The course specifically investigates how to craft compelling stories in an age where narratives can also be generated by AI. | |||||||||
| CHS7004 | Thesis writing in humanities and social sciences using Python | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | Korean | Yes | |
| This course is to write a thesis in humanities and social science field using Python. This course is for writing thesis using big data for research in the humanities and social sciences. Basically, students will learn how to write a thesis, and implement a program in Python as a research methodology for thesis. Students will learn how to write thesis using Python, which is the most suitable for processing humanities and social science related materials among programming languages and has excellent data visualization. Basic research methodology for thesis writing will be covered first as theoretical lectures. Methodology for selection of topics will be discussed also. Once a topic is selected, a lecture on how to organize related research will be conducted. In the next step, students learn how to write necessary content according to the research methodology. Then how to suggest further discussion along with how to organize bibliography to complete a theoretical approach. The basic Python grammar is covered for data analysis using Python, and the process for input data processing is conducted. After learning how to install and use the required Python package in each research field, the actual data processing will be practiced. To prepare for the joint research, learn how to use the jupyter notebook as the basic environment. Learn how to use matplolib for data visualization and how to use pandas for big data processing. | |||||||||
| CHS7007 | AI-Based Media Text Comprehension | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | Korean | Yes | |
| This course aims to equip students with the ability to critically analyze and understand various forms of media texts—such as news, advertisements, films, and social media—through the use of artificial intelligence (AI). Students will learn techniques in natural language processing (NLP), including sentiment analysis, keyword extraction, and text summarization, as well as methods for analyzing visual content using AI models like CNNs and GANs. The course also addresses issues of trustworthiness and ethical concerns related to AI-generated content. Combining theoretical instruction with practical application, students will complete hands-on assignments and projects using Python-based AI tools such as GPT and Gemini AI. | |||||||||
| CHS7008 | Strategic Decision-Making with AI | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | Korean | Yes | |
| This course equips students with the essential skills to make strategic decisions using generative AI. As technology rapidly transforms every industry, the ability to critically evaluate AI-generated information and integrate it into decision-making has become a core competency. This course addresses that need by preparing students to work with AI not just as a tool, but as a collaborative partner. Students will gain a foundational understanding of AI systems, particularly the workings of generative AI models. They will learn to analyze unstructured outputs such as text and predictions, assess data reliability, and identify biases. Ethical and responsible use of AI is emphasized to build both technical and social awareness. Going beyond traditional data analysis, the course explores human-AI collaboration in solving real-world problems. Students will examine decision-making case studies across industries including business, healthcare, finance, and policy. Through team-based projects, they will apply AI tools to complex strategic challenges. The curriculum reflects global academic standards, drawing inspiration from courses at MIT, Stanford, and Carnegie Mellon. By aligning with leading institutions, the course helps students build globally competitive capabilities. Ultimately, this course develops future-ready professionals who combine AI fluency with critical thinking and leadership. It is an essential foundation for navigating a world where AI shapes strategy. | |||||||||
| CNT3017 | Content Industry PBL | 3 | 6 | Major | Bachelor | Culture and Technology | - | No | |
| Students will do hands-on projects to develop technical knowledge and skills and the ability to understand how technology influences humans, design, and creative processes. Students will work with real-world problems, deal with developing fascinating cultural products or high-tech applications, and focus on having a social impact. To do so, Students will train to draw a hypothesis, market research, business communication skills, and finally develop business plans of their own. | |||||||||
| CNT3028 | Creating Social Media Star | 3 | 6 | Major | Bachelor | Culture and Technology | - | No | |
| What are the characteristics of successful YouTubers and Inflammers? How are the characteristics of celibacy in the existing pop culture different from those of the digital age? Which of the characteristics of the two world's celibacy are compatible and not possible? The class analyzes media and pop culture drivers who create popularity and fame, and the characteristics of platforms and content from the perspective of history, marketing, business and technology. | |||||||||
| CNT3042 | Creating a Social Media Star 2 | 3 | 6 | Major | Bachelor | Culture and Technology | - | No | |
| This class takes up where “Creating a Social Media Star (CNT3028)” left off. Students will practice the knowledge of “popularity,‘ ”influence,“ ”digital content planning,“ and ”digital channel management“ by actually opening and operating a social media channel. They will analyze diverse data from channel operation, and will be evaluated by ”how much the channel have grown its influence during the semester.“ | |||||||||
| CNT3044 | Interactive&Virtual Narrative | 3 | 6 | Major | Bachelor | Culture and Technology | - | No | |
| This class introduces the relationship between interactivity and storytelling. Students will analyze how an interactive structure may alter narrative. This class will explore conventional linear content and move on to nonlinear novels, theater/performance, games, interactive films and VR narratives. Particularly, this class will examine the characteristics of interactive media and the structural properties of narratives such as multiple points of view, disruptions of time/space, digression, alternate storylines, and audience participation. | |||||||||
| CNT3045 | Content Commerce | 3 | 6 | Major | Bachelor | Culture and Technology | - | No | |
| Many manufacturers and online shopping malls along with social media and portals are introducing their own “media commerce” services. This class introduces students to diverse content practices taking place in the commerce industry, investigates how media commerce differs from the conventional “TV home shopping” business. In the semester the students will produce content to sell their own goods (or the goods prepared by the department) to actually learn ther key success factors of content commerce. | |||||||||
| CNT3046 | Analyzing Social Data | 3 | 6 | Major | Bachelor | Culture and Technology | - | No | |
| This class introduces diverse data extractable from social media. Particularly “the structured data” (i.e., user traffic and other quantifiable data) and “the unstructured data” (i.e., user comments, interpreted sentiment) are examined. Students will learn how to collect, analyze, and interprete these data to identify social trends, project consumer behaviors, and enable more precise targeting. | |||||||||
| CON3032 | Consumer Big Data Analysis | 3 | 6 | Major | Bachelor | 2-4 | Consumer Science | Korean | Yes |
| Introduction to machine learning for consumer science. This course covers foundational concepts in machine learning such as overfitting, cross validation, and bias-variance tradeoff, and application of machine learning algorithms to consumer big data analysis. | |||||||||