For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| 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. | |||||||||
| ESM3083 | Introduction to AI & Practice | 3 | 6 | Major | Bachelor | 3-4 | Systems Management Engineering | - | No |
| Overall in the course, students will be exposed to various aspects of Artificial Intelligent (AI). As AI itself meant differently to different people, depending on their field of expertise and study, students will be introduced to various definitions and methods related to engineering. Generally, AI agreed to the division of AI into knowledge-based (where intelligence are entered or built into the system by gathering the information from experts) and the computational intelligent system (where intelligence are computed into a model based on a lot of past data available). In the class, students will be learned various technologies like rule-based system (RBS), search algorithms, uncertainty in RBS, fuzzy system, artificial neural network, and genetic algorithm. The course is intended to be theoretical as well as practical. To gain some practical knowledge, students are required to produce prototype systems for knowledge based and computational based AI. In completing the course assignment and tasks, students are required to work individually and/or as a group to be involved in problem-solving and making decisions. Students’ knowledge and ability are also tested in case studies, projects, interactive discussions, mid-term examination, and final examination. | |||||||||
| NAT7001 | AI-Assisted Research Methodology for Natural Sciences | 1 | 2 | Major | Bachelor/Master/Doctor | Science | Korean | Yes | |
| This course is an online research methodology course designed to help students in the College of Natural Sciences use generative AI and large language models effectively and responsibly throughout the research process. Rather than being limited to a specific major, the course covers common research tasks performed by natural science researchers, including research topic development, literature review, data organization, analytical support, academic writing and scientific figure preparation, presentation design, research ethics, and verification methods. Through this course, students will develop the ability to use generative AI not merely as a tool for generating answers, but as a research assistant for refining research questions, critically examining literature and data, logically communicating research findings, and verifying research outputs. | |||||||||
| SNT4027 | solar cell | 3 | 6 | Major | Bachelor/Master | Nano Science and Technology | - | No | |
| Introduction to the fabrication and operation of solar cells. Topics include fabrication of solar cells; device structures; operating principles; design of solar cells. | |||||||||