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 | - | No |
| 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. | |||||||||
| 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. | |||||||||
| 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. | |||||||||
| CHS2015 | AI-based Neuroscience and Neurotechnology | 3 | 6 | Major | Bachelor | 1-4 | Challenge Semester | - | No |
| This course will introduce fundamentals of how human brain works and the state-of-the-art of neuroscience research. This course will cover the convergence of cognitive neuroscience and neurotechnology with humanities and social sciences (e.g., brain-computer interface, neuromarketing, neurolinguistics, neuroergonomics, etc.), AI applications to advance neuroscience/engineering, and future directions through class discussions. This course aims for students to ① understand the literature in the fields of cognitive neuroscience and neurotechnology based on the understanding of humanities and social sciences; ② understand the state-of-the-art of AI and its applications to advance neuroscience; ③ articulate the domains and contexts in which cognitive neuroscience and neurotechnology may be effective; ④ develop an ability to lay out the open questions and address challenges in cognitive neuroscience and neurotechnology research today;and ⑤ prepare themselves to be more knowledgeable and proficient professionals. | |||||||||
| 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. | |||||||||
| 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 | |||||||||
| CHS7004 | Thesis writing in humanities and social sciences using Python | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| 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. | |||||||||
| CLA2003 | Reading the Literary Classics | 3 | 6 | Major | Bachelor | 2-4 | Liberal Arts | Korean,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. | |||||||||
| CLA3001 | Liberal arts Co-op 1 | 2 | 4 | Major | Bachelor | 3-4 | Liberal Arts | - | No |
| Field practice to utilize knowledge accumulated from classroom studies for real world problems(for 2 weeks) | |||||||||
| CLA3002 | Liberal arts Co-op2 | 3 | 6 | Major | Bachelor | 3-4 | Liberal Arts | - | No |
| Field practice to utilize knowledge accumulated from classroom studies for real world problems(for 4 weeks) | |||||||||