For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| BTH5094 | Therapeutic antibody | 3 | 6 | Major | Master/Doctor | Biopharmaceutical Convergence | - | No | |
| Antibody shows therapeutic activity through immune reaction, a natural phenomena. Therapeutic antibody represents biotherapeutics and leads biotherapeutic market. Hence, understanding therapeutic antibody is essential for understanding biotherapeutics. The class includes basic immunology essential to understand antibody, how to develop antibody, antibody surrogates, and the antigens for therapeutic antibodies. How to develop antibody will be the main contents, for example, phage display, animal-based antibody discovery, antibody optimization, strategy for therapeutic antibody discovery, etc. At last, examples of real therapeutic antibody discovery will be introduced. | |||||||||
| BTH5097 | Tissue Engineering for Drug Discovery | 3 | 6 | Major | Master/Doctor | Biopharmaceutical Convergence | English | Yes | |
| Tissue Engineering is a next-generation biotechnology to create human tissue surrogates in vitro by applying the development and regeneration process of the human body. Tissue Engineering is a promising platform for developing new drugs and it holds a great potential to serve as next-generation biopharmaceuticals for regenerative medicines. In this course, basic concepts/principles of tissue engineering and state-of-the-art tissue engineering strategies such as organoid/3D bioprinting will be covered. In addition, through case studies, tissue engineering techniques currently applied to the pharmaceutical industry will be covered. The goals of this course are as follows: 1) Understanding of tissue engineering principles and state-of-the-art tissue engineering technology, 2) Improving reading comprehension skills of original research articles, and 3) Setting biomedical research problems in real life and proposing problem solving methods using tissue engineering principles. | |||||||||
| CHS7001 | Introduction to Blockchain | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| This course deals with the basic concept for the overall understanding of the technology called 'blockchain'. We will discuss the purpose of technology and background where blockchain techology has emerged. This course aims to give you the opportunity to think about the limitations and applicability of the technology yourself. You will understand the pros and cons of the two major cryptocurrencies: Bitcoin and Ethereum. In addition, we will discuss the concepts and limitations about consensus algorithm (POW, POS), the scalability of the blockchain, and cryptoeconomics. You will advance your understanding of blockchain technogy through discussions among students about the direction and applicability of the technology. | |||||||||
| 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 | |||||||||
| CHS7004 | Thesis writing in humanities and social sciences using Python | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | - | No | |
| This course is to write a thesis in humanities and social science field using Python. This course is for writing thesis using big data for research in the humanities and social sciences. Basically, students will learn how to write a thesis, and implement a program in Python as a research methodology for thesis. Students will learn how to write thesis using Python, which is the most suitable for processing humanities and social science related materials among programming languages and has excellent data visualization. Basic research methodology for thesis writing will be covered first as theoretical lectures. Methodology for selection of topics will be discussed also. Once a topic is selected, a lecture on how to organize related research will be conducted. In the next step, students learn how to write necessary content according to the research methodology. Then how to suggest further discussion along with how to organize bibliography to complete a theoretical approach. The basic Python grammar is covered for data analysis using Python, and the process for input data processing is conducted. After learning how to install and use the required Python package in each research field, the actual data processing will be practiced. To prepare for the joint research, learn how to use the jupyter notebook as the basic environment. Learn how to use matplolib for data visualization and how to use pandas for big data processing. | |||||||||
| COV5005 | Advanced Individual Research Project(Ⅰ)1 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||
| COV5006 | Advanced Individual Research Project(Ⅰ)2 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||
| COV5007 | Advanced Individual Research Project(Ⅰ)3 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||
| COV5008 | Advanced Individual Research Project(Ⅰ)4 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||
| COV5009 | Advanced Individual Research Project(Ⅰ)5 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||
| COV5010 | Advanced Individual Research Project(Ⅰ)6 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||
| COV5011 | Advanced Individual Research Project(Ⅰ)7 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||
| COV5012 | Advanced Individual Research Project(Ⅰ)8 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||
| COV5013 | Advanced Individual Research Project(Ⅰ)9 | 3 | 6 | Major | Master/Doctor | 1-8 | SKKU Institute for Convergence | - | No |
| This course is intended for students that applied for the research-intensive degree program. The aim of this course is to learn the basics of convergence research based on his/her major, and the ultimate goal is to produce top-level research results. This course is designed to set up convergent research topics and conduct research under the instruction of a student’s co-advisor. Students have autonomy to organize their own curricula with any research activities such as joining labs, on-the-job experiences, field work, independent research, etc. | |||||||||