For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| 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 | |||||||||
| 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. | |||||||||
| DRM5024 | Ubiquitous Disaster Technology | 3 | 6 | Major | Master/Doctor | 1-8 | Interdisciplinary Program in Crisis, Disaster and Risk Management | - | No |
| In order to embody the U-disaster protection system, it needs a synchronization technology of VR·AR that can decide the exact position where the service or management should be performed. Moreover, disaster protection technology which is suitable for ubiquitous circumstance, real-time U-space technology that can maximize a service quality and realistic contents providing technology is necessary. This course deals with above mentioned ubiquitous technology for disaster prevention. | |||||||||
| ECA4702 | Advanced Foundation EngineeringⅠ | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
Civil, Architectural and Environmental System Engineering | - | No |
| Geotechnical aspects of the analysis, design, and construction of foundation systems and earth retaining structures: Analysis and design of shallow and Deep foundations including piles and caissons, Analysis and design of earth retaining structures including gravity and cantilever retaining walls, sheet pile walls and other systems, Analysis and design of Braced excavation, Analysis and design of reinforced earth structure. | |||||||||
| ECA4704 | Technology for Responding to Trace Organic Pollutants | 3 | 6 | Major | Bachelor/Master | 1-4 | Civil, Architectural and Environmental System Engineering | - | No |
| With rapid industrial development and urbanization, the generation and emission of new types of pollutants becomes a problem. It is especially important to remove emerging contaminants such as fine plastics and trace organic pollutants in water treatment process. In this course, the comprehend and treatment of these emerging contaminants as well as smart response technologies(SRT) to solve these problems are introduced. Several relevant case studies of deriving and applying the optimal SRT according to the type of emerging contaminants are introduced. - Current and emerging contaminants (fine plastic, trance organic contaminant etc.): case studies in terms of source, cause, fate & transport, problems, etc. - Smart response technology (AOP, adsorption, membrane and other emerging advaced technologies): case studies in terms of theory, process operation and maintenance, economics etc. | |||||||||
| ECA4707 | Tunnel and Underground Space | 3 | 6 | Major | Bachelor/Master | 1-4 | Civil, Architectural and Environmental System Engineering | - | No |
| This class deals with fundamental of tunnel and underground space system design technology. Detailed subjects include basics of rock mechanics and rock engineering, rock mass classification, shear strength and compressive behavior of soil due to underground excavation, tunnel design principle, arching theory, numerical analysis of tunnel, and Artificial Intelligence-based tunnel design. | |||||||||
| ECA4708 | Applied Statistical Hydrology | 3 | 6 | Major | Bachelor/Master | 1-8 | Civil, Architectural and Environmental System Engineering | - | No |
| This course offers free English lectures that focus on statistic-based techniques. All students are required to work on their own projects using statistical methodologies. The course aims to provide students with a thorough understanding of the properties and characteristics of water resources data. Subject Objectives: To improve the understanding of the characteristics of water resource data. To enhance statistical data analysis capabilities. To develop logical thinking skills based on statistics. Midterm and Finalterm exam or presentation would be done in this class to evaluate the grade of the students. And also the assignment will be given. | |||||||||
| ECA5304 | Special Topics of Structural Engineering Ⅱ | 3 | 6 | Major | Master/Doctor | 1-4 | Civil, Architectural and Environmental System Engineering | - | No |
| Improves an overall understanding of civil materials by oral and written presentations and discussion on several topics related to mechanical behaviors of steel, concrete, and composite materials. | |||||||||
| ECA5306 | Mechanical Behavior of Construction Materials | 3 | 6 | Major | Master/Doctor | 1-4 | Civil, Architectural and Environmental System Engineering | - | No |
| Develops an understanding of mechanical behavior of construction materials such as concrete and metals. Includes study of elastic deformation, yielding criteria, creep, fracture, and fatigue of the materials. | |||||||||
| ECA5314 | Advanced Construction Materials | 3 | 6 | Major | Master/Doctor | 1-4 | Civil, Architectural and Environmental System Engineering | - | No |
| Introduces manufacturing methods and properties of construction materials such as steel and concrete. Measures of strength and physical properties of steel and concrete specimens. | |||||||||
| ECA5318 | Plastic Analysis and Design | 3 | 6 | Major | Master/Doctor | 1-4 | Civil, Architectural and Environmental System Engineering | - | No |
| This course introduces basic theory of plastic analysis and design of structures. Topics to be covered include yield in material, plastic behavior of sections, plastic zone, plastic hinge, collapse condition, collapse mechanism, upper bound theory, lower | |||||||||
| ECA5407 | Seminar on Construction Engineering Method | 3 | 6 | Major | Master/Doctor | 1-4 | Civil, Architectural and Environmental System Engineering | - | No |
| Major construction methods and state-of-the-art technologies used contemporarily in construction projects are introduced through case studies. Features, pros and cons, future direction of those technologies are discussed and researched. This course could be provided through lecture series by practitioners and experts of construction and engineering firms. | |||||||||
| ECA5502 | Advanced Sustainable Design | 3 | 6 | Major | Master/Doctor | 1-4 | Civil, Architectural and Environmental System Engineering | Korean | Yes |
| The objective of this course is to provide students with an understanding of environmental design principles in architecture. Principles of life-cycle design and strategies to increase environmental sustainability in buildings are are insvestigated. It also examines energy-conscious design issues using a design problem in a studio format. This course presents design and modeling methods for predicting thermal and lighting behavior and introduces the latest building environmental technology. | |||||||||