For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| EME5308 | Combustion Processes | 3 | 6 | Major | Master/Doctor | 1-4 | Mechanical Engineering | English | Yes |
| This course will cover the fundamentals of combustion systems, and fire and explosion phenomena. Topics covered include thermochemistry, chemical kinetics, laminar flame propagation, detonations, energy and mass transport, and drop combustion. | |||||||||
| ERC5001 | Global Collaboration Research | 3 | 6 | Major | Master/Doctor | Engineering | Korean | Yes | |
| This class aims to enhance global competence as a researcher who study innovative growth fields through overseas dispatch of graduate students. Student’s who are dispatched overseas and carrying out joint research in world university will learn - to establish global network for future research - to strive for the creation of new industries in the field of sustainable development and innovative growth of mankind - to grow into global innovative leader with the competence of ‘Value creation’, ‘Convergence’, ‘Innovation’, and ‘Collaboration’ through innovation in creative convergence experiences that which cross the intercultural, interdisciplinary and intergeneration. In this class, students are expected to focus on projects during the overseas dispatch period to improve the quality of their research. Each researcher will present final report after they complete dispatch study and will be given their credit based on the presentation. | |||||||||
| ESM4013 | Web Information System | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
Industrial Engineering | - | No |
| This course deals with the technologies related to the building of web-based information systems. Some of the major topics covered in this course are information systems architecture under web environment, EDI (Electronic Data Interchange), DTD (Document Type Definition), application of XML, web publishing, linking database to the web, automatic retrieval and processing of web information, design and use of intelligent agent, strategic use of web information, and BPR and ERP under web environment. | |||||||||
| ESM4032 | Stochastic Processes | 3 | 6 | Major | Bachelor/Master |
3-4
1-4 |
Industrial Engineering | - | No |
| Theories and analyses of the stochastic processes occurring in industry are covered. | |||||||||
| ESM5002 | Advanced Simulation Methods | 3 | 6 | Major | Master/Doctor | 1-4 | Industrial Engineering | - | No |
| General issues on simulation methodologies and splicing a bridge between theory and simulation software will be discussed. New simulation languages(SLAM II) will be introduced. Major topics will be covered are: Random Number Generation, Random Variate Generation, Verification and Validation, Variance Reduction Techniques, Meta Modeling, and Simulation Output Analysis. | |||||||||
| ESM5079 | Service Strategy | 3 | 6 | Major | Master/Doctor | 1-4 | Industrial Engineering | - | No |
| This course deals with the fundamental concepts of service strategy and their application to real world problems. Topics include service vision, service strategy development, service strategy deployment, and strategy validity assessment. The strategic issues related to global service organizations are investigated in depth using various case studies. | |||||||||
| ESW4001 | Virtual Reality Theory | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | - | No | |
| Virtual reality is an interdisciplinary next-generation medium that fuses many different areas upon computer science and engineering. This course focuses on the technological aspects of virtual reality, and deals with the fundamentals of theories, hardware/software, and its applications. The major subjects include virtual reality systems, the basics of computer graphics and stereoscopic rendering, vision/auditory/haptic perception, 3D interaction and practical implementation techniques. | |||||||||
| ESW4004 | Principles of Distributed Computing | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | Korean | Yes | |
| A distributed system is a collection of independent networked computers that function as a single coherent system. With the advent of the fast interconnect and large datasets, a.k.a. Big Data, distributed systems are becoming more important and they are widely used in various domains including AI. The primary goal of this class is to learn key design principles of distributed systems and understand how distributed systems manage resources in a networked environment. Course topics include, but not limited to, communication protocols, processes/threads, naming, synchronization, consistency, and fault tolerance. | |||||||||
| ESW4006 | Information Visualization | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | Korean | Yes | |
| With the advances in data storing and processing technologies, the size of data humans confront is increasing at an unprecedented rate. Despite the ever-increasing data size, our perceptual and cognitive abilities stay relatively unchanged, leading to an information gap between humans and data. Information visualization provides one means of addressing such information overload, as well-designed visual representations can assist our perceptual and cognitive abilities to understand, analyze, and memorize the data. In this course, students will learn to 1) design, evaluate, and critique visualization designs, 2) comprehend the characteristics of humans' perception that underpin visualization, 3) understand novel visualization and interaction techniques, and 4) implement interactive data visualizations. The topics of this course will include but not limited to: - Foundations of Information Visualization, Exploratory Data Analysis (EDA), Visual Analytics - Data and Task Abstraction - Mark, Channel, Color, Perception, Interaction, and Animation - Tables, Maps, Networks, Text, and Uncertainty - Visualization for Large-scale and High-dimensional Data - Visualization for the Explainability and Trustworthiness of Machine Learning Methods | |||||||||
| ESW4008 | Data Science and Security | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | - | No | |
| This course is to learn about the AI security and privacy. Additionally, we study the role of AI, data and data analytics for security and privacy applications. This course focuses on applications of AI, machine learning and big data analytics to various security and privacy problems, using various data analysis and AI techniques to solve challenging security and privacy issues. | |||||||||
| ESW4025 | Artificial Intelligence Ethics | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | English | Yes | |
| With the current development of artificial intelligence, we can meet them in various parts of society. However, artificial intelligence is an amoral that cannot make ethical judgments on its own. Therefore, we need to understand and solve various ethical problems caused by artificial intelligence. In this class, we will look at the ethical problems, causes, and solutions of artificial intelligence. First, we will briefly learn about artificial intelligence and then look at the ethical problems they have. They can be largely divided into data, algorithms, and applications, so we will look at each of them. We will then look at the causes of these problems. In addition, we will look at algorithms and examples that actually solve them based on the analyzed problems and causes. | |||||||||
| ESW4026 | Computer Networks and Artificial Intelligence | 3 | 6 | Major | Bachelor/Master | Computer Science and Engineering | - | No | |
| This course aims at the improvement of the capability to apply Artificial Intelligence (AI) technology to the Internet where AI is one of core technologies in the 4th industrial revolution. For this aim, it explains the fundamental protocols and systems of computer networks and security, and the AI technology which can be applied to the computer networking technology. To prepare for 6G network era, it deals with Intent-Based Networking (IBN), Cloud-based Security Services, Intelligent Internet of Things, and Wireless Networking for autonomous vehicles. Especially, AI-based networking and security technologies are handled for 6G core networks. Also, this course teaches students the protocol layers such as data link layer, network layer, transport layer, and application layer. The contents of this course consist of introduction for 1 week, 6G network technologies for 5 weeks, and computer network layers for 8 weeks. As the expected benefits of this course, the students not only learn the foundational knowledge of computer networks and security, but also, for the 4th industrial revolution era, they can be educated up to SW-AI experts who can graft the technologies of the AI and Machine Learning (ML) to the computer networking field. | |||||||||
| ESW5012 | Topics in Real-Time Systems for Software Platforms | 3 | 6 | Major | Master/Doctor | 1-4 | Computer Science and Engineering | English | Yes |
| This course studies classic real-time systems' theories, and then investigates the-state-of-the-art issues of real-time systems towards supporting software platforms. First, fundamental scheduling theories are covered, including scheduling for the basic real-time task model in uniprocessor/ multiprocessor/cluster platforms, as well as that for the fork-join model and synchronization. Based on the theoretical background, up-to-date papers for real-time systems are studied so as to support software platforms. | |||||||||
| ESW5024 | Advanced Data Analysis | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | English | Yes | |
| This class is to explore the most common methods used in the field of data analysis and statistical modeling to analyze real-world data, i.e., data summaries, visualization, prediction, and as tools for scientific inference and causal data analysis. The course deals with benchmark data that displays non-linear patterns, frequency data, count data, and longitudinal data. Assuming that students are familiar with basic probability and mathematical statistics, the course covers several topics related to VC theory, convergence, point and interval estimation, maximum likelihood, hypothesis testing, data reduction, Bayesian inference, nonparametric statistics, and bootstrap resampling, dependent data analysis, and causal inference. By completing the course, students with a data analysis problem will be able to select the appropriate statistical/analytical methods to critically evaluate the resulting statistical models, and report the results. The course's primary goal is to familiarize graduate students with the modern methods of data analysis and help them to choose the right method for the research job at hand (rather than distorting the problem to fit the methods you happen to know). This is crucial for having high-quality research results. | |||||||||
| ESW5025 | Infra Networks and Security | 3 | 6 | Major | Master/Doctor | Computer Science and Engineering | - | No | |
| This course introduces technologies and standards of infrastructure networks and security. This course explains the technologies of networks and applications in the network infrastructure (e.g., cloud, Internet of Things, and vehicular networks), and also the technologies of security and privacy in this infrastructure. The contents of this course are as follows. - Week 1: Introduction to Infra Networks and Security - Week 2: Internet and Computer Networks - Week 3: Software-Defined Networking (SDN) - Week 4: Network Functions Virtualization (NFV) - Week 5: OpenStack-Based Cloud Systems - Week 6: Cloud-Based Security Service Systems - Week 7: YANG-Based Data Modeling - Week 8: Term Project Proposal - Week 9: NETCONF-Based Network Management - Week 10: Internet-of-Things (IoT) Networking - Week 11: IoT Applications - Week 12: IoT Security - Week 13: Vehicular Networking - Week 14: Vehicular Network Applications and Security - Week 15: Term Project Presentation This course will be delivered in the format of a flipped class. It has four homeworks and one term project. | |||||||||