For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| BPC5013 | 3D printed chip design and fabrication | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | English | Yes |
| The main objective of the course is to introduce 3D bioprinting used in lab-on-chips to graduate students having a background in engineering. The course should familiarize the students with the techniques used in 3D bioprinting and show them how 3D printing technology pervades throughout various regenerative medicine. | |||||||||
| BPC5014 | IQB Colloquim1 | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | English | Yes |
| The main objective of the course is for IQB students to learn research topics in multiple areas, widen their insights, and consequently elevate their research. This course is composed of weekly seminars provided by speakers from SKKU and others with introductory to and recent publications in their multidisciplinary areas. | |||||||||
| BPC5015 | IQB Colloquim2 | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | English | Yes |
| The main objective of the course is for IQB students to learn research topics in multiple areas, widen their insights, and consequently elevate their research. This course is composed of weekly seminars provided by speakers from SKKU and others with introductory to and recent publications in their multidisciplinary areas. | |||||||||
| CHS2003 | Robust System Design with Big Data Analytics and Artificial Intelligence | 2 | 4 | Major | Bachelor | 1-4 | Challenge Semester | - | No |
| In this course, the fundamental theories and methodologies on big-data analytics and artificial intelligence (AI) algorithms for prognostics and health management (PHM) of engineering systems are mainly covered. More specifically, the reliability analysis, sensor-based big-data collection, signal processing, statistical feature extraction and selection, and AI-based modeling are studied, and the hands-on practices are also carried out. In addition, various case examples are introduced to study the robust engineering system design using the big-data analytics and AI algorithms. | |||||||||
| CHS2017 | A new human, phono sapiens Experience Design | 3 | 6 | Major | Bachelor | 1-4 | Challenge Semester | - | No |
| As humans started using smartphones, they are experiencing changes in consumption psychology, consumer behavior, and market ecosystems due to rapidly changing lifestyles. This represents a new type of human, the main protagonist of the revolution, called Phono Sapiens. As consumption civilization changes, we learn about digital transformation and changes in business models driven by the development and evolution of big data, artificial intelligence, and digital platforms. We analyze and learn the direction of digital experience design (Digital Experience Design) based on digital transformation. Companies provide and understand the direction of new business innovation and change in accordance with rapidly changing trends for Phono Sapiens, the new consumers. | |||||||||
| CHS7002 | Machine Learning and Deep Learning | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| This course covers the basic machine learning algorithms and practices. The algorithms in the lectures include linear classification, linear regression, decision trees, support vector machines, multilayer perceptrons, and convolutional neural networks, and related python pratices are also provided. It is expected for students to have basic knowledge on calculus, linear algebra, probability and statistics, and python literacy. | |||||||||
| CHS7002 | Machine Learning and Deep Learning | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| This course covers the basic machine learning algorithms and practices. The algorithms in the lectures include linear classification, linear regression, decision trees, support vector machines, multilayer perceptrons, and convolutional neural networks, and related python pratices are also provided. It is expected for students to have basic knowledge on calculus, linear algebra, probability and statistics, and python literacy. | |||||||||
| CHS7003 | Artificial Intelligence Application | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| Cs231n, an open course at Stanford University, is one of the most popular open courses on image recognition and deep learning. This class uses the MOOC content which is cs231n of Stanford University with a flipped class way. This class requires basic undergraduate knowledge of mathematics (linear algebra, calculus, probability/statistics) and basic Python-based coding skills. The specific progress and activities of the class are as follows. 1) Listening to On-line Lectures (led by learners) 2) On-line lecture (English) Organize individual notes about what you listen to 3) On-line lecture (English) QnA discussion about what was listened to (learned by the learner) 4) QnA-based Instructor-led Off-line Lecture (Korean) Lecturer 5) Team Supplementary Presentation (Learner-led) For each topic, learn using the above mentioned steps from 1) to 5). The grades are absolute based on each activity, assignment, midterm exam and final project. Class contents are as follows. - Introduction Image Classification Loss Function & Optimization (Assignment # 1) - Introduction to Neural Networks - Convolutional Neural Networks (Assignment # 2) - Training Neural Networks - Deep Learning Hardware and Software - CNN Architectures-Recurrent Neural Networks (Assignment # 3) - Detection and Segmentation - Generative Models - Visualizing and Understanding - Deep Reinforcement Learning - Final Project. This class will cover the deep learning method related to image recognitio | |||||||||
| CHS7003 | Artificial Intelligence Application | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| Cs231n, an open course at Stanford University, is one of the most popular open courses on image recognition and deep learning. This class uses the MOOC content which is cs231n of Stanford University with a flipped class way. This class requires basic undergraduate knowledge of mathematics (linear algebra, calculus, probability/statistics) and basic Python-based coding skills. The specific progress and activities of the class are as follows. 1) Listening to On-line Lectures (led by learners) 2) On-line lecture (English) Organize individual notes about what you listen to 3) On-line lecture (English) QnA discussion about what was listened to (learned by the learner) 4) QnA-based Instructor-led Off-line Lecture (Korean) Lecturer 5) Team Supplementary Presentation (Learner-led) For each topic, learn using the above mentioned steps from 1) to 5). The grades are absolute based on each activity, assignment, midterm exam and final project. Class contents are as follows. - Introduction Image Classification Loss Function & Optimization (Assignment # 1) - Introduction to Neural Networks - Convolutional Neural Networks (Assignment # 2) - Training Neural Networks - Deep Learning Hardware and Software - CNN Architectures-Recurrent Neural Networks (Assignment # 3) - Detection and Segmentation - Generative Models - Visualizing and Understanding - Deep Reinforcement Learning - Final Project. This class will cover the deep learning method related to image recognitio | |||||||||
| COV7001 | Academic Writing and Research Ethics 1 | 1 | 2 | Major | Master/Doctor | SKKU Institute for Convergence | Korean | Yes | |
| 1) Learn the basic structure of academic paper writing, and obtain the ability to compose academic paper writing. 2) Learn the skills to express scientific data in English and to be able to sumit research paper in the international journals. 3) Learn research ethics in conducting science and writing academic papers. | |||||||||
| DES4001 | Convergence Capstone Design | 3 | 6 | Major | Bachelor/Master | Design | Korean | Yes | |
| Various students from different majors, Design, Art, IT, Business, Engineering, and etc., are gathered to study the development of future new technology, services and creative design products. Also, they are processing the prototype of the study and supporting the application of effective ideas. The purposes of this study are to overcome the present level of studies' approaches and create new and innovative values and to acquire creativeness, Problem Based Learning skill, and ability to conduct Team Project. | |||||||||
| DES4001 | Convergence Capstone Design | 3 | 6 | Major | Bachelor/Master | Design | Korean | Yes | |
| Various students from different majors, Design, Art, IT, Business, Engineering, and etc., are gathered to study the development of future new technology, services and creative design products. Also, they are processing the prototype of the study and supporting the application of effective ideas. The purposes of this study are to overcome the present level of studies' approaches and create new and innovative values and to acquire creativeness, Problem Based Learning skill, and ability to conduct Team Project. | |||||||||
| EAM7001 | Plasma Processes and Equipment | 3 | 6 | Major | Bachelor/Master/Doctor | 3-4 | Advanced Materials Science and Engineering | Korean | Yes |
| This class will discuss theoretical and experimental backgrounds on processing, diagnostic, and equipment technologies related to plasma deposition and etching applied to semiconductor, displays, and various nanodevice processing. The contents are as follows; 1) Gas Collision Processes, 2) Vacuum and Parts, 3) Plasma Technology, 4) DC, RF, High Density Plasmas, 5) Plasma Dignostics, 6) Plasma Deposition, 7) Plasma Etching, 8) Seminar on Recent Plasma Application Technologies | |||||||||
| EAM7001 | Plasma Processes and Equipment | 3 | 6 | Major | Bachelor/Master/Doctor | 3-4 | Advanced Materials Science and Engineering | Korean | Yes |
| This class will discuss theoretical and experimental backgrounds on processing, diagnostic, and equipment technologies related to plasma deposition and etching applied to semiconductor, displays, and various nanodevice processing. The contents are as follows; 1) Gas Collision Processes, 2) Vacuum and Parts, 3) Plasma Technology, 4) DC, RF, High Density Plasmas, 5) Plasma Dignostics, 6) Plasma Deposition, 7) Plasma Etching, 8) Seminar on Recent Plasma Application Technologies | |||||||||
| ECE4247 | Power Electronics System Analysis | 3 | 6 | Major | Bachelor/Master | 1-4 | Electrical and Computer Engineering | - | No |
| Inverters and converters play an important role to operate fuel cell systems, hybrid electric vehicles, and etc. In this subject, design and control of various power conversion circuits according to the application conditions. Completing this subject, one can handle hardwares and softwares for power conversion circuits and can utilize the theory and technique for industry applications | |||||||||