For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| AAI2011 | Introduction to System Programming | 3 | 6 | Major | Bachelor | Applied Artificial Intelligence | Korean | Yes | |
| System software such as operating systems, device drivers, compilers, etc. provide an environment in which computer hardware can be controlled directly and application software can be run. These system software are often implemented in C language. This course covers system software theory and design/implementation methodology based on C language. It also learns how to understand and use UNIX/Linux environments. Provides experience in developing system software for various system resource management, such as process/thread management and network communication. | |||||||||
| 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 | |||||||||
| CSE3036 | Seminar in Computer Engineering | 1 | 2 | Major | Bachelor | 3-4 | English | Yes | |
| This class provides broad knowledge about many fields of computer engineering. Various subjects are selected which are currently hot issues in computer engineering, and invited talks are given about the selected subjects. | |||||||||
| 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. | |||||||||
| ECE4272 | Advanced Convergence Capstone Design | 3 | 6 | Major | Bachelor/Master | Electrical and Computer Engineering | Korean | Yes | |
| Design addresses problems faced by local communities with a focus on design, experimentation, and prototyping processes. Particular attention is placed on constraints faced when designing for handicapped and elderly people. Multidisciplinary teams work on projects in collaboration with community partners, field practitioners, and experts in relevant fields. Topics covered include design for affordability, design for sustainability, and strategies for working effectively with community partners and customers. Students work in multidisciplinary teams on term-long projects in collaboration with community partners, field practitioners, and experts in relevant fields. Students may continue projects begun in other problem-based learning projects (such as in convergence capstone design, global convergence capstone design). | |||||||||
| EEE3011 | Digital Signal Processing | 3 | 3 | Major | Bachelor | 3-4 | Electronic and Electrical Engineering | Korean | Yes |
| The topics to be covered are : Analysis and process techniques used in computer processing of signals. Analog to digital conversion. Recursive digital filters, and matched filters. Time series analysis of waveforms, z-transforms, and Fast Fourier transforms (FFT) for digital signal analysis, complex demodulaion and data compression. Cepstrum tecnique and spectral estimation. | |||||||||
| EEE3012 | Digital Communication | 3 | 3 | Major | Bachelor | 3-4 | Electronic and Electrical Engineering | Korean | Yes |
| This course covers the essential theories and principles of digital and data communication. The topics to be included are ; digital network configuration, circuit and packet switching system, digital representation of information, synchronous and asynchronouse time division multiplexing, network architecture modem, layered protocol, packet data network, local area network, and the concept of ISDN (Integrated Services Digital Network). | |||||||||
| EEE3024 | Introduction to Automatic Control | 3 | 3 | Major | Bachelor | 3-4 | Electronic and Electrical Engineering | Korean,English | Yes |
| This course provides an introduction to automatic control of linear dynamic systems. The topics include definition of input-output and state variables, mathematical modeling of control systems based on physical laws, block diagram representation of systems, transfer function and Laplace transform, state space representation of dynamic systems. Feedback control concept, stability of systems, transient and steady state responses of systems in the time domain, and basic controller formsare treated and computer simulations of dynamic control systems using control software toolbox are assigned as homework. | |||||||||
| EEE3032 | Communication Systems | 3 | 3 | Major | Bachelor | 3-4 | Electronic and Electrical Engineering | Korean | Yes |
| This course covers diverse topics related to the communication, and the topics related to the application of the communication theory. The topics to be covered include communication channel model, fading phenomena, receiver struc- ture, basics of mobile communication, basics of satellite communication, wave propagation model, communication traffic model, and synchronization theory. | |||||||||
| EEE3049 | Introduction to Computer Networks | 3 | 6 | Major | Bachelor | 3-4 | Electronic and Electrical Engineering | - | No |
| There are details about the upper layer, protocols, standards, and interfaces, based on the basic concept of data communication. This course is concerned with the mode of operation of the different types of data network that are used to interconnect a distributed community of computers and the various interface a standards and protocols associated with them. Also, describe the function and operation of the additional protocols that are needed to enable a set of aplication programs to communicate with one another to perform specific distributed application functions. | |||||||||
| EME3022 | Measurement Engineering | 3 | 6 | Major | Bachelor | 2-4 | Mechanical Engineering | English | Yes |
| This course covers the basic principles of measurement systems in engineering application. Fundamentals of measurement, modeling and characteristics of measurement systems are studied and sensors, electrronic circuit, components, operational amplifier are introduced, and the practical case studies for measuring dimension angle, velocity, force, flow rate, temperature and power are treated. method & principles of measurement at not only existing sensor but also MEMS sensor, and data-handling, database, system diagnosing for measuring data are studied for using computer | |||||||||
| ERC2007 | Engineering Numerical Analysis | 3 | 6 | Major | Bachelor | 2-3 | Engineering | Korean,English | Yes |
| We deal with the major sources of errors in numerical methods, the approximated solution of non-linear equations, the solution of simultaneous linear equations, polynomial interpolation, numerical differentiation, numerical integration, and curve fitting to measured data as a technique to solve the mathematical problems in scientific and engineering area. | |||||||||
| ERC2008 | Introduction to Management of Technology | 3 | 6 | Major | Bachelor | 2-3 | Engineering | Korean | Yes |
| This subject handles various theory and practical application about MOT. Main contents are Test of technical innovation process, R&D strategy, patent administration, R&D project plan establishment, Market analysis, Technology Assessment, Technology Contract, Technology Management. | |||||||||