For more details on the courses, please refer to the Course Catalog
Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
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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. | |||||||||
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 | |||||||||
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. | |||||||||
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. | |||||||||
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. | |||||||||
DES4001 | Convergence Capstone Design | 3 | 6 | Major | Bachelor/Master | Design | Korean | Yes | |
Various students from different majors, Design, Art, IT, Business, Engineering, and etc., are gathered to study the development of future new technology, services and creative design products. Also, they are processing the prototype of the study and supporting the application of effective ideas. The purposes of this study are to overcome the present level of studies' approaches and create new and innovative values and to acquire creativeness, Problem Based Learning skill, and ability to conduct Team Project. | |||||||||
ERP4001 | Creative Group Study | 3 | 6 | Major | Bachelor/Master | Korean | Yes | ||
This course cultivates and supports research partnerships between our undergraduates and faculty. It offers the chance to work on cutting edge research—whether you join established research projects or pursue your own ideas. Undergraduates participate in each phase of standard research activity: developing research plans, writing proposals, conducting research, analyzing data and presenting research results in oral and written form. Projects can last for an entire semester, and many continue for a year or more. SKKU students use their CGS(Creative Group Study) experiences to become familiar with the faculty, learn about potential majors, and investigate areas of interest. They gain practical skills and knowledge they eventually apply to careers after graduation or as graduate students. | |||||||||
FDM5002 | Special Topics in History of Oriental Costume | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
Historical study of clothing and ornaments in Oriental countries. | |||||||||
FDM5003 | Special Topics in History of Westernl Costume | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
Survey of important periods in the history of costume and their relationship to the times and their importance in the evolution and inspiration of modern dress. | |||||||||
FDM5004 | A Study of Korean Costume | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
This course studies the aesthetic and functional part of general Korean costume. | |||||||||
FDM5007 | Special Topics in Fashion Design | 3 | 6 | Major | Master/Doctor | 1-4 | - | No | |
This course helps the students to become qualified as a fashion designer with the basis for understanding the concept of design and the various aspects of design. Each student will practice design considering the principles and requisites for fashion design. | |||||||||
FDM5013 | Contemporary Fashion Design Analysis | 3 | 6 | Major | Master/Doctor | 1-4 | Korean | Yes | |
A study of relationship between the features of modern design and its socio-cultural background. | |||||||||
FDM5020 | Special Topics in Dress Aesthetics | 3 | 6 | Major | Master/Doctor | 1-4 | Korean | Yes | |
A study of the nature of aesthetic values of apparel, grounds for criticism and function of the apparel. |