For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ESM5213 | Special Topics in Engineering Mechanics | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course discusses the fundamental concepts and applications of engineering mechanics for solving engineering problems. This course also reviews system modeling approaches and their industrial applications based on understanding of system dynamics. | |||||||||
| ESM5214 | PHM Seminar | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course introduces the industrial applications of PHM technology across industries, such as manufacturing, energy, and military, and the challenges towards industrial application. | |||||||||
| ESM5215 | Seminars on Smart Manufacturing | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| This course offered to understand paradigm and technical issues of Smart Manufacturing by short lectures and seminars. It includes new paradigm of next generation manufacturing engineering and production system, smart manufacturing, Industry 4.0, and smart factory. | |||||||||
| ESM5219 | Smart Product Design & Manufacturing | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| This course deals with practical techniques necessary for product development and production in the manufacturing industry. Examples from the field are used to explain how to design and manufacture products based on data to solve field-oriented problems. This starts with the understanding of the organizational structure, the roles of each of those organizations, and the relationship among those organizations within a manufacturing company. Practical examples are used to illustrate how to incorporate various design tools for product development, such as simulation, VE (Value Engineering), optimization technique, TRIZ, and 6-sigma including the development process from preliminary research to mass production and essential elements of product design, The course also covers basic manufacturing processes, the concept of smart factory, innovative manufacturing activities in the field, and data-based manufacturing management, focused on electronics. Furthermore, it introduces the roles of the quality, purchase, design, and product planning organizations that must cooperate during product development. Finally, it deals with the strategic mindset and the how-to on preparing materials necessary for engineering practice. | |||||||||
| ESM5220 | Advanced in Digital Twin and Advanced Treatment | 3 | 6 | Major | Master/Doctor | 1-8 | Korean | Yes | |
| This course offered to understand backgrounds, basic theories, and applications, and technical issues of cyber-physical system, digital twin and advanced treatment by lectures and problem-based learning classes. - Product/Factory design and operation - Advanced treatment - Smart manufacturing and smart factory - Cyber physical system, digital twin | |||||||||
| ESM5221 | Advanced in Smart Manufacturing and Advanced Treatment | 3 | 6 | Major | Master/Doctor | 1-8 | Korean | Yes | |
| This course offered to understand backgrounds, basic theories, and applications, and technical issues of smart manufacturing and advanced treatment by problem-based learning classes. - Product design and development, PLM, advanced treatment - Factory design and production operation, manufacturing engineering and information system - Smart Manufacturing and Smart Factory - IIoT, Smart Sensor, Cloud, Platform, Cyber Physical System, Digital Twin | |||||||||
| ESM5222 | Stochastic Optimization | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| This course is about stochastic optimization and will mainly be on stochastic programming. Many problems in business, engineering, and science involve uncertainties, but optimization of such complex systems is often done in practice with deterministic model parameters. Stochastic programming extends deterministic optimization by incorporating random variables and probabilistic statements. The aim of the course is to study (i) modeling, (ii) theory, and (iii) solution techniques for such problems. | |||||||||
| ETM5107 | Seminars on patent statistics and bibliometric analysis | 3 | 6 | Major | Master/Doctor | 1-4 | Management of Technology | Korean | Yes |
| This course is designed to guide graduate students to learn patent statistics and bibliometric analysis techniques for research on innovation management and policy. In the first half of the course, patent statistics and bibliometric analysis techniques for research on innovation will be introduced. In the last half of the course, students will be required to review preapproved research papers that employed patent statistics and bibliometric analysis as the main research methods. | |||||||||
| GWR5022 | Membrane Water Treatment | 3 | 6 | Major | Master/Doctor | 1-8 | Water Resources | Korean | Yes |
| Give a lecture about the water treatment process using the membrane. Study about the theories and designing of drinking water treatment, sewage treatemtn, desalination and reused water. | |||||||||
| GWR5023 | Advanced Water Treatment Unit Operation | 3 | 6 | Major | Master/Doctor | 1-8 | Water Resources | Korean | Yes |
| Give a lecture about the advanced water treatment applied to drinking water treatment and reused water. Study about physical, chemical and biological treatment process, and mass transfer and modeling of water reuse | |||||||||
| GWR5076 | Ultrapurewater Technology | 3 | 6 | Major | Master/Doctor | 1-8 | Water Resources | - | No |
| It is a subject that lectures theoretical and practical contents on essential processes, maintenance processes, and risk management processes for ultrapure water manufacturing processes essential for semiconductor manufacturing, high-purity pharmaceutical manufacturing, and fine chemical manufacturing. It lectures on the theory of deagasing process and degasing membrane to remove gas in water, MF and UF membrane to remove particles, RO membrane to remove ionic substances, cation exchange resin and anion exchange resin, and UV oxidation used for oxidation purposes. | |||||||||
| ICE2003 | Probability and Random Processes | 3 | 6 | Major | Bachelor | 1-4 | Information and Communication Engineering | Korean,Korean | Yes |
| Introduction to basic probability theory and modeling random processes for the analysis and design of electric system. Topics may include axiomatic foundation of probability, conditional probability, indepedence, random variables, distribution function, density functions, characteristic functions, expectation and random process. | |||||||||
| ICE3043 | Introduction to Smart Car Engineering | 3 | 6 | Major | Bachelor | 3-4 | Information and Communication Engineering | Korean | Yes |
| This course deals with a broad outline of smart cars. In order to understand the basic fundamentals of an automobile, this course firstly introduces the state-of-the-art technologies which are currently being developed. In addition, an overall automobile architecture including driving, transmission, and chassis systems is introduced. Then, the driver assistance system for providing the comfort to operators is informed. This course also presents the recent development trend of smart cars in terms of in-vehicle softwares and electronics including sensors, actuators, and embedded boards. Moreover, the novel technologies for control softwares of vehicle system, vehicle networking, and application level softwares of connected cars are covered. Finally, in this course, we debate on the social, legal, and ethical issues of the smart car technology for finding solutions of its faster development. | |||||||||
| ICE3051 | Autonomous driving capstone design | 3 | 6 | Major | Bachelor | 3-4 | Information and Communication Engineering | Korean,Korean | Yes |
| A capstone design course that performs a team project to develop an autonomous car. In this class, students form a team with other students to develop a self-driving car with Jetson nano board and sensors, such as camera. In this class, students learn AI programming and problem-solving skills related to autonomous driving. | |||||||||
| ISS3222 | Introduction to Machine Learning | 3 | 6 | Major | Bachelor | English | Yes | ||
| Covers fundamental concepts for intelligent systems that autonomously learn to perform a task and improve with experience, including problem formulations (e.g., selecting input features and outputs) and learning frameworks (e.g., supervised vs. unsupervised), standard models, methods, computational tools, algorithms and modern techniques, as well as methodologies to evaluate learning ability and to automatically select optimal models. Applications to areas such as computer vision (e.g., characte r and digit recognition), natural language processing (e.g., spam filtering) and robotics (e.g., navigating complex environments) will motivate the coursework and material. | |||||||||