For more details on the courses, please refer to the Course Catalog
Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
---|---|---|---|---|---|---|---|---|---|
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. | |||||||||
CHY4004 | Advanced Analytical Chemistry Ι | 3 | 6 | Major | Bachelor/Master | 1-4 | Chemistry | English | Yes |
In the class of Instrumental Analysis in undergrauate course deals generals of chemical instruments in many aspects. Theses days, many of universities update their undergraduate curricular in different ways. So quite many students did not have chance to take Instrumental Analysis class during their undergraduate course. In this aspect, we offer this class as one of our graduate core courses to provide basic instrumental analysis as wel as application of instruments for chemical analysis. | |||||||||
CHY5011 | Molecular Spectroscopy | 3 | 6 | Major | Master/Doctor | 1-4 | Chemistry | - | No |
In this course, theoretical background and experimental methods of various molecular spectroscopy will be lectured. After reviewing some fundamentals of quantum theory, electromagnetic radiation and its interaction with atoms and molecules, general features of experimental methods, molecular symmetry, rotational spectroscopy, vibrational spectroscopy, electronic spectroscopy, photoelectron and related spectroscopy will be studied. | |||||||||
CHY5072 | Spectroelectrochemistry | 3 | 6 | Major | Master/Doctor | 1-4 | Chemistry | - | No |
Voltage, current, charge are the classic parameters in electrochemistry. The classic methods cannot produce information about the redox reaction at near the electrode surface at molecular level. In situ methods of UV/VIS, IR, Raman, X-ray spectroscopy are covered in this class. | |||||||||
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. | |||||||||
EAM4014 | Global Techno Management | 2 | 4 | Major | Bachelor/Master | 1-4 | Advanced Materials Science and Engineering | - | No |
The requirement and problem of the real technology in the industrial field are analyzed by inviting specialists and CEOs to learn the ability of solving the industrial problem. Also, management and commencement of an enterprise are studied. | |||||||||
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 | |||||||||
ECH4009 | Introduction to Quantum Chemistry | 3 | 6 | Major | Bachelor/Master | Chemical Engineering | - | No | |
The goal of the course is to provide students with a fundamental understanding of the quantum chemical description of atoms and molecules. Particular emphasis is placed on the understanding of chemical bonding and reactivity, together with the theoretical basis for optical spetroscopy. The course also provides the fundamental quantum chemical background required for further courses in molecular modeling, NMR spectrocopy, inorganic chemistry and physical organic chemistry. | |||||||||
ECH4010 | Special Topics in Chemical Industry | 3 | 6 | Major | Bachelor/Master | Chemical Engineering | - | No | |
This lecture will be given both by professors and by engineers from chemical industry. Main topics include chemical industry of Korea, polymer products and technology, biochemical products, water treatment technology, and energy storage devices. Students will be graded based on team projects and exams. | |||||||||
ECH5017 | Advanced Nano - Processing Technology | 3 | 6 | Major | Master/Doctor | 1-4 | Chemical Engineering | - | No |
Nano processing technologies required for various nano-devices are discussed. These include thin film deposition processes, patterning technologies, etching, self assembled monolayer (SAM), and carbon nanotube processing. Recent research and development trend are also discussed. | |||||||||
ECH5029 | Special Topics in Composite Materials | 3 | 6 | Major | Master/Doctor | 1-4 | Chemical Engineering | Korean | Yes |
In this class, the physical properties of composite materials composed of polymers and metal or ceramic materials. The methods for estimation of mechanical strength of composit materials will be carefully discussed with several examples. The mechanical properties, such as, toughness, aging process, impact resistance will be discussed. | |||||||||
ECH5051 | Special Topics I on Semiconductor Chemical Processing | 3 | 6 | Major | Master/Doctor | 1-4 | Chemical Engineering | Korean | Yes |
In this course, various topics on the semiconductor processing will be discussed from the bird's eye view on the semiconductor processing and detailed descriptions for each topic. The semiconductor processing includes CVD (chemical vapor deposition), etching process, etc. Other processing techniques will be also discussed on theoretical analysis and actual applications. This course explains the prospects and trends on the semiconductor industry as well. |