For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| CCS2001 | A View of Culture | 3 | 6 | Major | Bachelor | 2-3 | Cross-cultural Studies | Korean | Yes |
| It aims to provide the fundamental cultural concepts for comparative culture. Through various ways of analyzing and understanding culture, students are encouraged to understand culture from various viewpoints and to establish a basic view of culture. | |||||||||
| CCS3011 | Techno-Cultural Studies | 3 | 6 | Major | Bachelor | 3-4 | Cross-cultural Studies | Korean | Yes |
| This course focuses on learning the viewpoint of Techno-Cultural studiest through various theories and modern phenomenon. After exploring how technology has influenced on the change of society from the basis, we expect students will expand the range of thought to individual subject and object. We will go through philosophy of technology and handle 'artificial intelligence', 'post-human', 'techno feminism', from the perspective of 'science and technology studies' and 'cultural studies'. | |||||||||
| CHS2002 | Data Science and Social Analytics | 1 | 2 | Major | Bachelor | 1-4 | Challenge Semester | - | No |
| This course is intended to examine human behaviors and social phenomena through the lens of data science. Students also may learn online data collection and analysis in social media spaces. It deals with both theory and practice, but relative portion may change in each semester without prior notice. | |||||||||
| 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. | |||||||||
| CHS2012 | IoT Project | 2 | 4 | Major | Bachelor | 1-4 | Challenge Semester | - | No |
| It is a course for students who are not familiar with software and hardware, but who are interested in Internet of Things area. It aims to provide easy and convenient steps of the area, including education of C language basics and various digital/analog sensor control conducted with a toolkit such as Arduino. Communication skills and cooperative spirit can be obtained by carrying out IoT projects through group activities. | |||||||||
| 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. | |||||||||
| CHS2019 | Information and Communication Technology Based on Quantum Mechanics | 1 | 2 | Major | Bachelor | Challenge Semester | Korean | Yes | |
| In the first half, basic physics lectures such as electron and photon, particle and wave duality, quantum superposition, entanglement, uncertainty principle, quantum tunneling effect, and Schrödinger equation, Maxwell's wave equation, and basic mathematics lectures such as Hilbert space, Bloch sphere, and bra and ket vector, which are essential for understanding qubits and quantum superposition, are fundamentally educated for understanding the information and communication technologies based on quantum mechanics. In the second half, current five types of qubit generation methods based on mechanical conservation using inductor and capacitor, quantum gates, quantum circuits, their quantum computer applications, sensitivity increased quantum sensors, and basic principles and current technologies of innovative quantum cryptography and quantum teleportation are taught. | |||||||||
| 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 | |||||||||
| 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. | |||||||||
| CLA2003 | Reading the Literary Classics | 3 | 6 | Major | Bachelor | 2-4 | Liberal Arts | Korean | Yes |
| This course is devoted to understanding the literary classics by reading and discussing a variety of representative works from Eastern and Western traditional and modern cultures. It requires a substantial amount of reading, writing, participation in discussions, and (possibly) individual presentations to the class. Timely reading is essential for class discussions, and students are expected to read at least one book every two weeks. The students are encouraged to articulate the ways literary work reflects the historical period and the culture that produced it; and more importantly, why this work is still relevant. | |||||||||
| CLA2006 | Humanities and entrepreneurship | 1 | 2 | Major | Bachelor | Liberal Arts | - | No | |
| The role of humanities in starting and managing a company is very important. This class explores cases in which humanities are applied in corporate start-ups and management, and learns that humanities thinking can be applied to corporate management. In addition, through historical examples, we explore the rise and fall of a company, learn how humanities helped lead a company, and how it played a role in escaping a company's crisis through various cases. It also has an opportunity to broaden its perspective on corporate management while exploring cases of not only domestic companies but also global companies. | |||||||||
| CLA2007 | Major Exploration for College of Liberal Arts | 2 | 4 | Major | Bachelor | 1-2 | Liberal Arts | Korean | Yes |
| This course is for students who wish to major or double major in the 10 departments of the College of Liberal Arts. It is a major exploration course in the Department of Korean Language and Literature, the Department of English Language and Literature, the Department of French Language and Literature, the Department of Chinese Language and Literature, the Department of German Language and Literature, the Department of Russian Language and Literature, the Department of Chinese Literature, the Department of History, the Department of Philosophy, and the Department of Library and Information Science. The class will introduce the curriculum of each department and the career path after graduation. | |||||||||
| CLA3001 | Liberal arts Co-op 1 | 2 | 4 | Major | Bachelor | 3-4 | Liberal Arts | Korean | Yes |
| Field practice to utilize knowledge accumulated from classroom studies for real world problems(for 2 weeks) | |||||||||