For more details on the courses, please refer to the Course Catalog
Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
---|---|---|---|---|---|---|---|---|---|
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 | |||||||||
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 | |||||||||
COV3028 | Practical Patent Law for Inventors | 3 | 6 | Major | Bachelor | SKKU Institute for Convergence | - | No | |
Under conventional education system, a class which teaches capability to do creative invention is divided from a class which teaches capability to help inventors to protect inventions as patents. This class, as commingling such two classes, trains inventors who can exploit their inventions, based on: on the whole process of invention, always the perspective of patent protection must be applied; patent-based perspective can enable inventors make better inventions; a good invention without being a strong patent cannot be commercially successful, etc. Specifically, being taught are: prior art search for establishing direction of R&D; evaluation of patentability of an invention; his invention’s infringement of another’s patent right, agreement of a license contract, etc. In addition, this class enables such students who are preparing the “Patent Attorney” examination to grasp basic concepts of the patent law. | |||||||||
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. | |||||||||
DES2027 | Expression & Material 1 | 3 | 6 | Major | Bachelor | 1-2 | Design | Korean | Yes |
Cultivate attitude of formatively observe the objects, as well as cultivate accurately expressing ability objective form of the object has and the quality of creative expression together with the characteristic comprehension utilizing diversified expressing materials. | |||||||||
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. | |||||||||
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. |