For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| SFC6003 | Doctoral Thesis Research 2 on Smart Factory | 3 | 6 | Major | Doctor | Korean | Yes | ||
| This course is to acquire research credits by individual research for the preparation of doctoral dissertations in the Department of Smart Factory Convergence. The individual research include technology review, planning of research methology, data acquisition and analysis using experimental and numerical technologies, derivation of conclusion and doctoral thesis writing. | |||||||||
| SFC7001 | Smart Factory Convergence Capstone Design 1 | 3 | 6 | Major | Bachelor/Master/Doctor | Korean | Yes | ||
| This corporate-sponsored projects course in smart factory is an industry-university partnership that integrates design, manufacturing, service engineering, and business realities into the engineering curriculum. Students take their project ideas from concept to reality by designing, prototyping, and simulating real solutions in state-of-the-art facilities. This course challenges students to apply the knowledge and tools acquired during their undergraduate education to solve real-world engineering problems. | |||||||||
| SFC7002 | Smart Factory Convergence Capstone Design 2 | 3 | 6 | Major | Bachelor/Master/Doctor | Korean | Yes | ||
| This course provides a unique opportunity for industry to partner with our university to educate the next generation of world-class engineers. Interdisciplinary teams of students work together to tackle projects sponsored by industrial clients. These teams collaborate with engineering faculty, who serve as mentors and advisers, to devise ideas to solve engineering problems. | |||||||||
| SPE5007 | Seminars on Smart Power Engineering | 3 | 6 | Major | Master/Doctor | Smart Power Engineering | - | No | |
| This class is to acquire knowledges on smart power engineering through seminars of experts on key issues in power generation and technologies of 4th industrial revolution. Various topics will be covered in the seminars including up-to-date energy policy, new power generation facilities, virtual plant, diagnostics and life-time prediction of plant equipment based on artificial intelligence and big data technologies. The class also include overseas excursion to advanced power plants. | |||||||||
| SUP5001 | Deep Neural Networks: Theory and Applications | 3 | 6 | Major | Master/Doctor | 1-4 | Superintelligence Engineering | - | No |
| This course covers deep learning based on artificial neural network which is advanced on various industrial. This course, especially, give students basic understanding of modern neural networks and their applications in computer vision and natural language understanding. Students learn about Convuloutional networks, RNNs, LSTM, Dropout and more. This course introduceds the major technology trens driving Deep Learning. | |||||||||