For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| CHS5006 | Optimization and performance evaluation of 3D printing | 3 | 6 | Major | Master/Doctor | 1-4 | Challenge Semester | - | No |
| Evolution of 3D printing application area is slow due to difficulty in developing contents, optimization and evaluation deposit process. We will discuss optimization techniques and evaluation of deposit process for DED based powder metal 3D printing. A real data set will be used for application of theory learned from the class. Furthermore, deep learning and machine learning techniques will be also covered. | |||||||||
| 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 | - | 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. | |||||||||
| 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. | |||||||||
| DRM5001 | International Disaster Management | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | - | No |
| This course is designed for people interested in disasters from a research or policy perspective and for those who may be charged with responsibility for on-the-scene intervention. The semester will begin with an overview of risk, vulnerability, resilience and then focus on disaster institutions, policy, and politics. We will conclude by examining organizational and individual behavior in high-stress situations. Throughout the semester, particular attention will be paid to how disaster management efforts can increase the vulnerability of some populations or can promote widespread resilience. | |||||||||
| DRM5002 | Safety Management | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | - | No |
| The goal of this topic is to teach basic principles of system safety, including accident analysis, hazard analysis, design for safety, human factors and safety, controlling safety during operations, and management of safety critical projects and systems. While you will learn what is currently done today, you will also learn new techniques that are proving to be more powerful and effective than the traditional safety engineering approaches. | |||||||||
| DRM5004 | law of Disaster | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | - | No |
| This subject deals with the contents of emergency law to understand the characteristics of law that is related with safety purpose of life and property. In addition, the more general goals of this course are to provide the student with the following contents to help develop his or her potential: - more advanced study in laws related to emergency, disaster and security, etc. - improvement in social interaction skills and understanding disaster related problems | |||||||||
| DRM5005 | Urban disaster prevention | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | - | No |
| This course deals with definitions of disaster and other related terms like hazard, vulnerability and prevention in urban areas. It includes existing disaster prevention system, disaster prevention projects, urban disaster prevention and mitigation facilities hierarchy location problem modeling, etc. Moreover it also addresses types of disaster and discusses the trends of the occurrence of disasters to introduce students the basic concepts of the subject matter. | |||||||||
| DRM5007 | Crisis and Emergency Management | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | - | No |
| Risk management planning is the process of deciding how to approach, plan and execute the risk management activities for a project. The risk management approach may include decisions about the organization, staffing of the risk management activity, selection of the appropriate methodology, the sources of data to identify risk, and the time frame for the analysis. It is important to plan for the remaining processes of risk management so the level, type, and visibility of risk management are commensurate with both the risk and importance of the project to the organization. | |||||||||
| DRM5008 | Natural disaster reduction technology | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | Korean | Yes |
| Floods, draughts, cyclones, earthquakes, landslides, and tsunamis – such natural hazards are some of humanity's eternal scourges. A natural disaster takes place when society meets the natural hazard. Modern society provides efficient means to evacuate and shelter in emergency situations but it is also becoming more vulnerable from its dependence of complex societal and technological infrastructures. A natural disaster often incurs very large financial, environmental, and human losses that are seldom indifferent to social position, age, or gender. This course deals with above mentioned topics and give a practical computer simulation technique. | |||||||||
| DRM5011 | Geographic Information Systems for Emergency Management | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | Korean | Yes |
| Effective utilization of satellite positioning, remote sensing, and GIS in disaster monitoring and management requires research and development in numerous areas, including data collection, information extraction and analysis, data standardization, organizational and legal aspects of sharing of remote sensing information. This course provides a solid overview of what is being developed in the risk prevention and disaster management sector like GIS-based analysis for emergency management; domain-specific GIS applications; hands-on GIS software training; case studies on different aspects of emergency and disaster management. | |||||||||
| DRM5018 | Information Technology in Crisis and Emergency Management | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | Korean | Yes |
| The role of information in crisis and response management; determining disaster and crisis information requirements; information technologies applied to crisis, disaster, and emergency management; causes and effects of information breakdowns during crises and disasters. | |||||||||
| DRM5020 | Discipline of Crisis Preparedness and Response | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | Korean | Yes |
| Current preparedness and response programs. Mitigation, preparedness, and response requirements to manage crisis incidents within the context of all-hazard emergency management. Case studies. | |||||||||