For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| ERC5003 | Interdisciplinary research in global collaboration 2 | 3 | 6 | Major | Master/Doctor | 1-8 | Engineering | - | No |
| This class is aiming to foster graduate students as a global researcher by pursuing top-tier interdisciplinary research with global collaborators. In addition, the students will improve their own global competence to become a global innovative leader by establishing global academic networks. | |||||||||
| ERC5004 | Practical joint research in Global | 3 | 15 | Major | Master/Doctor | Engineering | - | No | |
| This class aims to enhance global competence as a researcher who study innovative growth fields through overseas dispatch of graduate students. | |||||||||
| ERC5005 | Machine Learning Essentials for Engineers | 3 | 6 | Major | Master/Doctor | Engineering | - | No | |
| As interest in artificial intelligence and machine learning grows, this course is designed to offer mathematical insights into machine learning techniques other than deep learning, enabling students to comprehend and effectively apply them. The course covers a range of topics including Imbalanced Learning, Bayesian Neural Networks, Monotonic Neural Networks, Neural Additive Models, Gaussian Process, Ensemble Learning, Expectation and Maximization, Neighbor Embedding, and more. This will facilitate students' understanding of machine learning-related research papers and equip them to solve real-world engineering problems in their respective fields of study. | |||||||||
| ERC7001 | Understanding and Utilizing the Metaverse Platform | 3 | 6 | Major | Bachelor/Master/Doctor | Engineering | - | No | |
| The main purpose of this course is training that equips students with metaverse-based business or service planning capabilities based on understanding of the technical elements consisting of the metaverse and hands-on experiences with major platforms and related devices. Opportunities to understand the characteristics and uses of each technical component, to study the cases of major services, and to identify strengths and weaknesses from the user's point of view through experience are given, and furthermore, the ability to derive creative ideas for the use and improvement of metaverse services is cultivated. do. | |||||||||
| ERC7002 | Understanding and Utilizing NFT | 3 | 6 | Major | Bachelor/Master/Doctor | Engineering | - | No | |
| The main purpose of this course is to educate students to have business or service planning skills using NFT based on understanding of the concept and underlying technology of NFT, related digital economic ecosystem, examples of NFT projects, and hands-on practice of NFT production and sales. It includes a basic understanding of blockchain and cryptocurrency, which are the base technologies of NFT, and digital art and digital assets, which are the major existing applications. Through learning about major project cases, legal considerations, market analysis tips, and technology trends, students will develop the ability to derive creative ideas for a wide range of future uses. | |||||||||
| ERP4001 | Creative Group Study | 3 | 6 | Major | Bachelor/Master | - | No | ||
| This course cultivates and supports research partnerships between our undergraduates and faculty. It offers the chance to work on cutting edge research—whether you join established research projects or pursue your own ideas. Undergraduates participate in each phase of standard research activity: developing research plans, writing proposals, conducting research, analyzing data and presenting research results in oral and written form. Projects can last for an entire semester, and many continue for a year or more. SKKU students use their CGS(Creative Group Study) experiences to become familiar with the faculty, learn about potential majors, and investigate areas of interest. They gain practical skills and knowledge they eventually apply to careers after graduation or as graduate students. | |||||||||
| ESC5015 | Introduction to Thermoelectric Materials Devices | 3 | 6 | Major | Master/Doctor | 1-8 | Energy Science | - | No |
| The subject studies the characteristics and synthesis of new functional thermoelectric materials which are based on conventional thermoelectric materials, nano, and fusion technology. Plus, various applications with thermoelectric materials will be discussed. | |||||||||
| ESC5187 | Advanced Low-Dimensional Heterostructures and Electrical Devices | 3 | 6 | Major | Master/Doctor | 1-8 | Energy Science | English | Yes |
| This course covers the design, physical properties, and applications of low-dimensional materials (e.g., graphene, molybdenum disulfide) and heterostructures, which are central to modern electronics and nanotechnology. It explores the electronic, optical, and thermal properties of these materials and structure, presenting methodologies for designing next-generation high-performance electronic devices and sensors. Specifically, the course includes topics such as quantum mechanical analysis, band structure engineering, interface property analysis, the fabrication of state-of-the-art two-dimensional devices including ferroelectric transistors, and technologies for future low-energy computing platforms. Through this course, students will gain an understanding of the latest research trends, acquire specialized knowledge required for advanced electronic device development, and cultivate creative problem-solving skills. | |||||||||
| ESM5109 | Patents and Entrepreneurship1 | 3 | 6 | Major | Master/Doctor | 1-4 | Industrial Engineering | Korean | Yes |
| The important issues and process of filing patents will be lectured in this class. Also, entrepreneurship using patents will be studied. The related laws will be reviewed, and actual case studies will be carried out. | |||||||||
| SDE5041 | Advanced Semiconductor Technology | 3 | 6 | Major | Master/Doctor | Semiconductor and Display Engineering | Korean | Yes | |
| The purpose of this course is to enhance theoretical understanding and cultivate practical ability of the latest semiconductor technology. This lecture covers semiconductor design, process and S/W by inviting executives and engineers from Samsung electronics DS, a global integrated device manufacturer. | |||||||||
| SNT4027 | solar cell | 3 | 6 | Major | Bachelor/Master | Nano Science and Technology | English | Yes | |
| Introduction to the fabrication and operation of solar cells. Topics include fabrication of solar cells; device structures; operating principles; design of solar cells. | |||||||||
| SNT5056 | Computational Science and Simulation | 3 | 6 | Major | Master/Doctor | 1-8 | Nano Science and Technology | English | Yes |
| This course gives an introduction to the basic methods in computational science and engineering, and an overview of the recent progress in scientific computing. It covers techniques used in modeling physical systems numerically and analyzing data. | |||||||||
| SNT5059 | Micro.nano thermal fluid engineering | 3 | 6 | Major | Master/Doctor | 1-8 | Nano Science and Technology | - | No |
| System design and manufacturing technology using micro/nano thermal-fluid engineering is a core technology to produce elements in MEMS, electronics, thermal energy, optics, and medical science. In this course, the latest work in heat transfer and fluid flow in micro- and nanoscale structures is presented. Course contents: miniature and microscale energy systems, nanostructures for thermoelectric energy, heat transport in superlattices and nanowires, thermomechanical formation and thermal detection of polymer nanostructures, two-phase flow microstructures in thin geometries, and numerical issues related to modeling and numerical implementations of flow and heat transfer at micro- and nanoscales. | |||||||||
| SUP5009 | Bioelectronic Devices and Intelligent Information Processing | 3 | 6 | Major | Master/Doctor | 1-2 | Superintelligence Engineering | - | No |
| The course covers the flexible electronic/bioelectronic materials and functional devices. Furthermore, various fabrication methods and characteristic analyses regarding soft electrodes, sensors, and non-volatile memories will be addressed. In addition, this course covers diverse artificial intelligence applications for effectively achieving high-fidelity physiological signals and biomedical images. For example, one topic is to discuss recent progress and limitation of sensors, memory devices, and artificial intelligence and predict their future prospects. The one goal of the course is to develop the ability of solving issues via various engineering aspects. | |||||||||