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Chemical Engineering

For more details on the courses, please refer to the Course Catalog

교육과정
Code Course Title Credit Learning Time Division Degree Grade Note Language Availability
BIO3004 Microbiology 3 6 Major Bachelor 2-3 Biological Sciences Korean Yes
Through microorganisms, the basic principles that govern the mistery of life as well as their practical applications toward human welfare will be taught. This introductory microbiology course will cover both the basic and applied asp-ects of microbiology. It will includes various subjects of microbiology such as structure and function of microbial cells, methodologies used in microbiology, growth and control of microorganisms, microbial biotechnology, industrial micro-biology, medical microbiology, microbial ecology, and microbial classifications.Concurrent registration with Microbiology Laboratory course is strongly recommended.
CHS2001 New humanity Phono Sapiens created by Smartphone 1 2 Major Bachelor 1-4 Challenge Semester - No
The humanity which have begun using smartphones are showing changes in consumer psychology, consumer behavior and market ecosystems due to rapidly changing lifestyles. This is Phono Sapiens, the new humanity is the hero of the revolution. The purpose of this course learn about the changes in business models due to the development of big data, artificial intelligence, and digital platforms by the change of consumption civilization. And it analyzes the development direction of continuously developing 5G, Internet of Things, robot, drone, autonomous vehicle, and smart factory. On this basis, companies present and understand new business innovation and directionality of change for new consumers called phono sapiens
CHS2002 Data Science and Social Analytics 1 2 Major Bachelor 1-4 Challenge Semester - No
This course is intended to examine human behaviors and social phenomena through the lens of data science. Students also may learn online data collection and analysis in social media spaces. It deals with both theory and practice, but relative portion may change in each semester without prior notice.
CHS2003 Robust System Design with Big Data Analytics and Artificial Intelligence 2 4 Major Bachelor 1-4 Challenge Semester Korean Yes
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.
CHS2008 The Fourth Industrial Revolution and Start-up Business 1 2 Major Bachelor 1-4 Challenge Semester Korean Yes
The fourth industrial Revolution is regarded as a key driving force to lead the new national growth method and changes the industrial structure. Therefore, major advanced economies are already proactively focusing on creating new business models in the fourth industrial revolution. On the other hand, the korea response system to the fourth industry and human resource development performance are considered insufficient. This subject is to aware of the necessity of Startiup a business in the era of the Fourth Industrial Revolution for lower-grade students at universities and to explain the fourth industrial revolution technology. Based on this background knowledge, students will learn business model development theory, startup team building, and how to draw up a business plan. In particular, this subject will secure successful start-up cases or related videos to encourage students fun and eventually cultivate basic skills to start Business.
CHS2009 Creative Ideation 2 4 Major Bachelor 1-4 Challenge Semester - No
Most people think that creativity is closely related to something new, unique and original. But we have no idea how to do if we actually think up creative ideas, which has never been existed, on our own. Let's take note of the well-known old saying, there is nothing new under the sun. We should change our perspective on creativity. There is common and distinct patterns in those things considered to be creative. This course introduce the common patterns of creative ideation with a lot of examples. Major topics include systematic inventive thinking, creative ideation codes, biomimicry, creativity in culture and arts.
CHS2012 IoT Project 2 4 Major Bachelor 1-4 Challenge Semester - No
It is a course for students who are not familiar with software and hardware, but who are interested in Internet of Things area. It aims to provide easy and convenient steps of the area, including education of C language basics and various digital/analog sensor control conducted with a toolkit such as Arduino. Communication skills and cooperative spirit can be obtained by carrying out IoT projects through group activities.
CHS2015 AI-based Neuroscience and Neurotechnology 3 6 Major Bachelor 1-4 Challenge Semester Korean Yes
This course will introduce fundamentals of how human brain works and the state-of-the-art of neuroscience research. This course will cover the convergence of cognitive neuroscience and neurotechnology with humanities and social sciences (e.g., brain-computer interface, neuromarketing, neurolinguistics, neuroergonomics, etc.), AI applications to advance neuroscience/engineering, and future directions through class discussions. This course aims for students to ① understand the literature in the fields of cognitive neuroscience and neurotechnology based on the understanding of humanities and social sciences; ② understand the state-of-the-art of AI and its applications to advance neuroscience; ③ articulate the domains and contexts in which cognitive neuroscience and neurotechnology may be effective; ④ develop an ability to lay out the open questions and address challenges in cognitive neuroscience and neurotechnology research today;and ⑤ prepare themselves to be more knowledgeable and proficient professionals.
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.
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
CHS7004 Thesis writing in humanities and social sciences using Python 3 6 Major Bachelor/Master/Doctor Challenge Semester Korean Yes
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.
CHS7004 Thesis writing in humanities and social sciences using Python 3 6 Major Bachelor/Master/Doctor Challenge Semester Korean Yes
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.