For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| CEK5123 | Reading of the Essential Writings of Hundred Schools of Thoughts(zhuzi baijia) | 3 | 6 | Major | Master/Doctor | 1-4 | Confucian Studies, Eastern Philosophy and Korean Philosophy | - | No |
| This course aims to investigate philosophical differences and similarities between pre-Qin thoughts including Confucianism, Mohism(墨家, Mojia), Daoism(道家, Daojia) and Legalism(法家, Fajia) by reading their original texts widely. Students thus would be able to learn the basic philosophical foundations of East Asian Philosophy. Through this, students are to research in priority the central and philosophical themes, which constituted Hundred Schools of Thought, such as the transition of the relationship between Heaven(天, Tien) and Human(人, Ren), differences in ethical point of views, and its corresponding changes in social ideologies, etc. | |||||||||
| CHS5005 | AI Startup and Entrepreneurship | 3 | 6 | Major | Master/Doctor | 1-4 | Challenge Semester | - | No |
| Recent years have witnessed a rapid increase in the number of so-called AI startups with AI as their core value, as the scope of AI's application across all industries has expanded significantly. This is gaining popularity not only in Korea, but globally as well. However, there are no theoretical or empirical guidelines regarding the entrepreneurial skills and business models that AI startups in a hypercompetitive market should possess. It is extremely harsh for those AI startups that are actually traditional businesses dressed up to look like they use AI to to succeed in a very competitive market. For AI startups with inadequate business acumen, gaining a foothold on the market is also a daunting task. By focusing on the following three goals, henceforth, this course aims to assist the growing number of AI startups with their challenges. Firstly, it categorizes the various possible business models for AI startup companies. Secondly, it then examines some of the most prominent domestic and international cases to illustrate the various types of entrepreneurship that AI startups require to thrive. Thirdly, a hypothetical AI startup is created, on a team basis, using real-world software such as Landbot, Stable Diffusion, and a number of no-code ML/DL (machhine learning/deep learning). Then its business model and entrepreneurship are established; and its efficacy is evaluated. | |||||||||
| 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. | |||||||||
| COV7001 | Academic Writing and Research Ethics 1 | 1 | 2 | Major | Master/Doctor | SKKU Institute for Convergence | Korean | Yes | |
| 1) Learn the basic structure of academic paper writing, and obtain the ability to compose academic paper writing. 2) Learn the skills to express scientific data in English and to be able to sumit research paper in the international journals. 3) Learn research ethics in conducting science and writing academic papers. | |||||||||
| EAS5214 | Gender and East Asian Women | 3 | 6 | Major | Master/Doctor | 1-4 | East Asian Studies | Korean | Yes |
| The goal of this course is to examine how gender or femininity was represented in modern East Asian culture and what social, historical, and intellectual contexts it contained. Moreover, this course will take into account women's self-representation and its shifting modes by examining some historical events. | |||||||||
| LIS4006 | Advanced Management of Libraries | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
- | No | |
| Discussion of the general mnagement in the library, including planning, stoff, personnel, finance and appraisal. | |||||||||
| LIS4009 | Seminar on Information Behavior | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
- | No | |
| This course provides an comparative overview of theoretical approaches that are relevant to understanding human bevaviors. Special emphasis is on cybernetics based on cognitivism and general behaviorism. | |||||||||
| LIS4010 | Seminar on Information Society | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
- | No | |
| This seminar provides an intelligent survey of theories and practical issues related to scholarly and professional information services and institutions. | |||||||||
| LIS4011 | Advanced Information Literacy | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
- | No | |
| This seminar introduces history of information literary and explores different models and methodologies related to information literacy. | |||||||||
| LIS4013 | Knowledge Organization | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
- | No | |
| This course provides a liguistic foundation necessary for the systematic organization of knowledge. It also addresses knowledge structure, representation and meanings. | |||||||||
| LIS4014 | Seminar on Building and Managing Internet Services | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
- | No | |
| The seminar concentrates on the principles of good web design and information architecture and effective management of websites. Other topics include HTML, XML, SGML, Doublin, Core, Resource Description, Firework. | |||||||||
| LIS4017 | Advanced Archiving | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
- | No | |
| Seminar in archiving focuses on the issues concerning the care and preservation of archive and the better administration of archive repositories to encourage relevant research. | |||||||||