For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| BUS2005 | Consumer Behavior and Brand Marketing | 3 | 6 | Major | Bachelor | 1-4 | Business Administration | Korean,English | Yes |
| This course aims to study consumers' decision making process and the factors which affect the decision of consumers. In particular this course focuses on the brand strategy from perspective of brand managers. The contents of this course include consumer decision making process, brand strategy and consumer behavior brand equity build-up and leveraging strategy frame work of management etc. | |||||||||
| CHS2008 | The Fourth Industrial Revolution and Start-up Business | 1 | 2 | Major | Bachelor | 1-4 | Challenge Semester | - | No |
| The fourth industrial Revolution is regarded as a key driving force to lead the new national growth method and changes the industrial structure. Therefore, major advanced economies are already proactively focusing on creating new business models in the fourth industrial revolution. On the other hand, the korea response system to the fourth industry and human resource development performance are considered insufficient. This subject is to aware of the necessity of Startiup a business in the era of the Fourth Industrial Revolution for lower-grade students at universities and to explain the fourth industrial revolution technology. Based on this background knowledge, students will learn business model development theory, startup team building, and how to draw up a business plan. In particular, this subject will secure successful start-up cases or related videos to encourage students fun and eventually cultivate basic skills to start Business. | |||||||||
| CHS7001 | Introduction to Blockchain | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| This course deals with the basic concept for the overall understanding of the technology called 'blockchain'. We will discuss the purpose of technology and background where blockchain techology has emerged. This course aims to give you the opportunity to think about the limitations and applicability of the technology yourself. You will understand the pros and cons of the two major cryptocurrencies: Bitcoin and Ethereum. In addition, we will discuss the concepts and limitations about consensus algorithm (POW, POS), the scalability of the blockchain, and cryptoeconomics. You will advance your understanding of blockchain technogy through discussions among students about the direction and applicability of the technology. | |||||||||
| CHS7002 | Machine Learning and Deep Learning | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| This course covers the basic machine learning algorithms and practices. The algorithms in the lectures include linear classification, linear regression, decision trees, support vector machines, multilayer perceptrons, and convolutional neural networks, and related python pratices are also provided. It is expected for students to have basic knowledge on calculus, linear algebra, probability and statistics, and python literacy. | |||||||||
| CHS7003 | Artificial Intelligence Application | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| Cs231n, an open course at Stanford University, is one of the most popular open courses on image recognition and deep learning. This class uses the MOOC content which is cs231n of Stanford University with a flipped class way. This class requires basic undergraduate knowledge of mathematics (linear algebra, calculus, probability/statistics) and basic Python-based coding skills. The specific progress and activities of the class are as follows. 1) Listening to On-line Lectures (led by learners) 2) On-line lecture (English) Organize individual notes about what you listen to 3) On-line lecture (English) QnA discussion about what was listened to (learned by the learner) 4) QnA-based Instructor-led Off-line Lecture (Korean) Lecturer 5) Team Supplementary Presentation (Learner-led) For each topic, learn using the above mentioned steps from 1) to 5). The grades are absolute based on each activity, assignment, midterm exam and final project. Class contents are as follows. - Introduction Image Classification Loss Function & Optimization (Assignment # 1) - Introduction to Neural Networks - Convolutional Neural Networks (Assignment # 2) - Training Neural Networks - Deep Learning Hardware and Software - CNN Architectures-Recurrent Neural Networks (Assignment # 3) - Detection and Segmentation - Generative Models - Visualizing and Understanding - Deep Reinforcement Learning - Final Project. This class will cover the deep learning method related to image recognitio | |||||||||
| CHS7005 | Consumer Neuroscience | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| A new market and consumer research methodology, consumer neuroscience method, will be explored in this class. Understanding consumers’ brain responses to brand using eyetracker and functional near infraredspectroscopy experiments is a goal of this study. Eyetracking and fNIRS will provide a new means of measuring brand equity as consumers’ brain responses will reflect their attitude, engagement, and and loyalty. | |||||||||
| 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. | |||||||||
| CLA7101 | AI-Assisted Research Methods for Linguistic Data | 1 | 2 | Major | Bachelor/Master/Doctor | Liberal Art | Korean | Yes | |
| AI-Assisted Research Methods for Linguistic Data is an interdisciplinary course designed for undergraduate and graduate students who wish to conduct research using linguistic data. Through step-by-step, hands-on activities, students engage in the entire research process—from identifying a research topic to collecting and preprocessing data, conducting experiments, visualizing results, and writing an academic paper—with the support of generative AI and a variety of AI-assisted tools. Upon completing the course, students will be able not only to independently carry out the entire process of linguistic data research but also to effectively select and utilize appropriate AI tools at each stage. They will also develop the ability to critically evaluate AI-generated outputs and apply them to their research in an informed, responsible, and independent manner. | |||||||||
| CON2002 | Consumer Decision Making | 3 | 6 | Major | Bachelor | Korean | Yes | ||
| An interdisciplinary approach to consumer decision-making from economics, psychology, and sociology in order to explore principles underlying consumer decision-making. | |||||||||
| CON2005 | Consumer Demographics | 3 | 6 | Major | Bachelor | 2-3 | - | No | |
| Understands characteristics of different consumer types by demographic backgrounds in terms of consumer needs and psychology, consumer behavior, consumption economy, and consumption patterns and analyzes marketing strategies targeting each type of consumers. | |||||||||
| CON2008 | Household Asset Management | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| Learn about the fundamentals of the financial market, investment theory, financial tools for asset management which are applied to household financial planning. | |||||||||
| CON2009 | Insurance ＆ Retirement Planning | 3 | 6 | Major | Bachelor | 2-3 | English | Yes | |
| Study principals and methods of household risk management and practice financial planning for retirement. | |||||||||
| CON2010 | Analysis of Consumer Needs | 3 | 6 | Major | Bachelor | 2-3 | Korean | Yes | |
| Develop the abilities of generating ideas for new products and services by approaching tacit and latent levels of consumer needs in the bottom of consumers’ minds by applying newly developed human-centered design research methods. | |||||||||
| CON2011 | Consumption Economics | 3 | 6 | Major | Bachelor | 2-3 | English | Yes | |
| Equipped with capability of analyzing and evaluating consumption pattern and economic well-being, based on understanding of the market economy, social-demographic trends, and economic theories of consumer decision making. | |||||||||
| CON2031 | Financial Consumers and Behavioral Finance | 3 | 6 | Major | Bachelor | 2-4 | Korean | Yes | |
| Based on understanding the psychological aspects of financial consumers as household asset managers and financial market participants, learn their characteristics of financial behavior and seek measures to promote financial capabilities and financial welfare. | |||||||||