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. | |||||||||
| AIM4003 | Natural Language Processing Fundamentals | 3 | 6 | Major | Bachelor/Master | 1-4 | Artificial Intelligence | Korean | Yes |
| his course covers the overall content of theories and techniques for analyzing and generating natural languages. This course deals with NLP overview, text corpus lexical resources, preprocessing, POS tagging, text vectorization, document classification, syntax analysis, semantic analysis, word embeddings, summarization, deep learning based language models. After taking this course, students are expected to implement programs to solve text problems. To take this course, students are required to have sufficient knowledge in machine learning, deep learning, and Python programming. | |||||||||
| 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 | Computer Science and Engineering | 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. | |||||||||
| DES2033 | Design Procedures | 3 | 6 | Major | Bachelor | 2-3 | Design | Korean,English | Yes |
| This workshop class will introduce students to Adobe After Effects, one of the most popular and precise digital compositing, 2D animation and motion graphics software used in broadcast design, video and film production. We will explore program features that include keyframing, editing, masking, type, 3D environment and tools. Students will learn basic compositing using layers, the creation and animation of text as well as keyframe-based effects. | |||||||||
| DES3034 | Design Solution | 3 | 6 | Major | Bachelor | 3-4 | Design | - | No |
| In Digital age, our environment has changed dramatically. This course supports students in exercising design solving method through making the attractive packages within customized & companies' desire.In the class, students will have an experience many perspectives such as customer observation,research,designing,economy,engineering etc. | |||||||||
| DES3038 | Information Design | 3 | 6 | Major | Bachelor | 3 | Design | English | Yes |
| Scientific analysis and anaesthetic sense of information are the essential grounding for visual communication designers. This course aims to understand Information design concept and principle, study visual communication methods and visualization technique,and design creative visual designworks. In this subject students will study the principles and best practices of effective information design for both print and electronic media. The course includes such topics as information types, information categorization and hierarchies, types of organizational patterns, structured information design and technologies,informatics,contentmanagement,the principles of visual communication in the context of information design, visual diagramming,data visualization. | |||||||||
| DES3039 | Integrated Design Studio | 3 | 6 | Major | Bachelor | Design | Korean | Yes | |
| 1. This class is to understand different kinds of design concepts and application methods. Students are expected to create design output that integrated visual communication design area after taking the 3 years of major courses. 2. This class is to understand different kinds of design concepts and application methods. Students are expected to create design output that integrated surface design area after taking the 3 years of major courses. | |||||||||
| EAM4014 | Global Techno Management | 2 | 4 | Major | Bachelor/Master | 1-4 | Advanced Materials Science and Engineering | - | No |
| The requirement and problem of the real technology in the industrial field are analyzed by inviting specialists and CEOs to learn the ability of solving the industrial problem. Also, management and commencement of an enterprise are studied. | |||||||||
| 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). | |||||||||
| EDU3031 | Emotional Intelligence and Informatics | 3 | 6 | Major | Bachelor | 1-4 | Education | - | No |
| The ability to express and control our own emotions is important, but so is our ability to understand, interpret, and respond to the emotions of others. Emotional intelligence (EI) refers to the ability to perceive, control and evaluate emotions. researchers suggest that emotional intelligence can be learned and strengthened. Based on the model proposed by Salovey and Mayer, four different factors of emotional intelligence will be dealt with in this class: the perception of emotion, the ability reason using emotions, the ability to understand emotion and the ability to manage emotions. | |||||||||
| EEE2008 | Signals and Systems | 3 | 3 | Major | Bachelor | 2-3 | Electronic and Electrical Engineering | English | Yes |
| Fundamentals of the analysis and processing of continuous and discrete signals in both time and frequency domains. Linear Time Invariant (LTI) systems and filtering. convolution, Fourier Series(FS), Fourier Transform(FT), Transform(DFT), Introduction to analog and digital communications and the Sampling Theorem Computer based simulation and data processing are used to demonstraste the above concepts in a laboratory settings. | |||||||||