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Undergraduate

Department of Computer Science

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
AAI2011 Introduction to System Programming 3 6 Major Bachelor Applied Artificial Intelligence Korean Yes
System software such as operating systems, device drivers, compilers, etc. provide an environment in which computer hardware can be controlled directly and application software can be run. These system software are often implemented in C language. This course covers system software theory and design/implementation methodology based on C language. It also learns how to understand and use UNIX/Linux environments. Provides experience in developing system software for various system resource management, such as process/thread management and network communication.
AIM4001 Advanced Big Data Analytics 3 6 Major Bachelor/Master Artificial Intelligence - No
This course introduces fundamental data mining and machine learning techniques for big data analytics. The emphasis in the course will be learning key techniques that are required to extract meaningful information from big data, and developing scalable data mining algorithms for big data analytics. The first half of the course will cover various supervised and unsupervised machine learning methods (theoretical analysis of the methods and their practical applications), and the last half of the course will focus on scalable graph mining techniques with special emphasis on analyzing large-scale social networks. There will be one midterm, three assignments, and the final project where students will be expected to develop scalable algorithms for collecting and analyzing big data.
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 - 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.
CHS2004 Humanities and creative thinking 1 2 Major Bachelor 1-4 Challenge Semester - No
The fourth industrial revolution is expected to accelerate the development of a hyper-connected society. IT technologies will enable various applications in our society with intelligent network connecting human, data, and objects. In such environment, companies will continue to strive to discover value-adding services for customers. This course is intended to help students enhance the understanding of human(customer) instinct as well as business and creativity through the lens of humanities.
CHS2011 Engineering Ethics and Post-Confucianism in the AI era 2 4 Major Bachelor 1-4 Challenge Semester - No
In this class, we will ponder over various ethical problems that currently arise in the process of developing artificial intelligence, and consider what kind of ethics is required in the future society in which much more advanced forms of artificial intelligence will emerge. In addition, we will examine whether and how East Asian traditions, especially the Confucian tradition, can still provide ethical insights to our society in the AI era.
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.
CHS2013 The Convergence of Cognitive Neuroscience and Neurotechnology with Humanities and Social Sciences 3 6 Major Bachelor 1-4 Challenge Semester - No
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, neuroscience-based cognitive computing, neuroergonomics, etc.), their applications 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) articulate the domains and contexts in which cognitive neuroscience and neurotechnology may be effective; 3) develop an ability to lay out the open questions and address challenges in cognitive neuroscience and neurotechnology research today; and 4) prepare them to be more knowledgeable and proficient professionals.
CHS2014 Developing 21C Skills through Team Entrepreneurship 1 2 Major Bachelor 1-4 Challenge Semester - No
The 21st Century is the era of transformation, where the scope, depth, and speed of the change we face is beyond our understanding. Faced with the fundamental shift, the young generation must develop the 21C skills (communication, creativity, collaboration, and critical thinking & problem solving) as defined by OECD. This course emphasizes that individuals can acquire the 4C skills during the process of solving social problems in trust-based teams. This course provides both the tools to use in daily life and the background theories so that students can develop the 4C skills and create their own lives by challenging social problems.
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
COV3002 Ubiquitous Society and Communication Competency 3 6 Major Bachelor 3-4 SKKU Institute for Convergence - No
This course generally focuses on understanding the characteristics of ubiquitous society and also it focuses on developing a new communication skill which is demanded by society. Media revolution called 'Media2.0' brought about at large reform of the society, it has a significant influence on society. Eventually the course examines those changes and evolutions in our society and also what they really are. The course deals with understanding the digital technology and the ethical issues behind the digital technology as well. A discussion on media ecosystem will suggest a new level of social meaning of Communication.
CSE3036 Seminar in Computer Engineering 1 2 Major Bachelor 3-4 English Yes
This class provides broad knowledge about many fields of computer engineering. Various subjects are selected which are currently hot issues in computer engineering, and invited talks are given about the selected subjects.
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.