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. | |||||||||
| 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. | |||||||||
| ECE4223 | Semiconductor Process Technology | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | English | Yes |
| This course helps to understand the overall semiconductor processes by introducing the theory and the application of unit processes; photolithography, photo-mask, dry-etch, cleaning, chemical-mechanical polishing(CMP), diffusion and thin film, and module processes; transistor, isolation, capacitor, interconnection. This also suggests the direction of process technologies for the future generations. | |||||||||
| ECE4233 | Simulation Engineering of Electric Power Systems | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | - | No |
| The objective of this lecture is to present methods of power system simulation, particularly with the aid of a personal computer, in sufficient depth to give the student the basic technique at the graduate level. Main subjects are steady-state & transient power system simulation, fault modeling technique, FACT(flexible alternating current transmission) simulation and the usage of EMTP, ATP, PSCAD/EMTDC. | |||||||||
| ECE4237 | Robotics | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | - | No |
| This course discusses the kinematics and the dynamics of manipulators. The path planning of each joint and some control algorithms of manipulators are also discussed. | |||||||||
| ECE4238 | Linear Systems | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | English | Yes |
| Methods of analysis for continuous and discrete-time linear systems. Convolution, classical solution of dynamic equations, transforms and matrices are reviewed. Emphasis is on the concept of state space. Linear spaces, concept of state, modes, controllability, observability, state transition matrix, state variable feedback, compensation, decoupling are treated. | |||||||||
| ECE4245 | Automation and Design of Electric Power System | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | Korean | Yes |
| In many coutries, the electric supply industry is undergoing a significant restructuring that has only just begun. Fully competitive markets of electric energy are fairly recent phenomena, and the existing competitive markets have not experienced significant of resource shortages yet. This course deals with the basic principles of power system automation from the point view of the central control facilities under competitive environment. And it discusses central computers used to process power system economic operating data, present vital data to an operator, and allow the operator to implement commands to equipment field. Also it contains the economic load dispatch, the Gauss-Seidel, Newton-Raphson, and decoupled method to iteratively calculate network power flow. | |||||||||
| ECE4246 | Digital Control | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | - | No |
| Many industrial control systems include digital computers as an integral part of their operation. Recent trends toward digital control of dynamic systems, rather than analog control, is mainly due to the recent revolutionary advances in digital computers and to advantages found in working with digital signals rather than continuous-time signals. Also, the availability of low-cost microprocessors and microcomputers established a new trend for even small-scale control systems to include digital computers to obtain optimal performance. The main purpose of this course is to present a comprehensive treatment of the analysis and design of discrete-time control systems. In particular, this course provides clear and easy-to-understand explanations for concepts involved in the study of discre-time control systems. | |||||||||
| ECE4247 | Power Electronics System Analysis | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | - | No |
| Inverters and converters play an important role to operate fuel cell systems, hybrid electric vehicles, and etc. In this subject, design and control of various power conversion circuits according to the application conditions. Completing this subject, one can handle hardwares and softwares for power conversion circuits and can utilize the theory and technique for industry applications | |||||||||
| ECE4248 | Networked Control System | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | - | No |
| The characteristics of the networked control system(NCS) are explained and the design requirement of the NCS are suggested. We treat the topics of the stability of the NCS, robust controller design for the NCS and the scheduling techniques for performance improvement. The NCS implemented by CAN(Controller Area Network) is presented as an application case. | |||||||||
| ECE4249 | Computer Vision | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | Korean | Yes |
| This course focuses in the study of theories for image analysis. The first part consists of Image formulation model, early processing, boundary detection, region growing and segmentation, motion detection, merging and introduction of morphology. The second part, we cover basic concepts of statistical model, dis- criminant function, decision boundary and rules and neural network for visual pattern recognition. | |||||||||
| ECE4261 | Nano Device | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | English | Yes |
| In this course, we will cover many topics including the growth methods and the physical/electrical characteristic for sub-nanometer dimensional materials. With the basic knowledge on nano scale materials, we deal with the nano devices (e.g., memory, logic, display devices, etc.), nano structures and operation principles. | |||||||||