For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| DAI5008 | Advanced Reinforcement Learning | 3 | 6 | Major | Master/Doctor | 1-8 | - | No | |
| Reinforcement learning is one powerful paradigm for an enormous range of tasks, including robotics, game playing, consumer modeling and healthcare. In this class, we will provide a solid introduction to the field of reinforcement learning including Markov decision process, planning by dynamic programming, model-free prediction, model-free control, value function approximation, policy gradient methods, integrating learning and planning, explorat | |||||||||
| DAI5009 | Service marketing and AI | 3 | 6 | Major | Master/Doctor | 1-8 | English | Yes | |
| This class provides theoretical and practical understanding of service marketing while providing opportunities to apply AI technology in marketing. Students will learn the difference between service and tangible products and their marketing strategies. Through thorough understanding about service marketing and its core concepts, students will design AI applications that can promote customer value, customer satisfcation, productivity, and quality enhancement. Important contributing factors of competitive edge will be discussed and applied in designing AI applications. | |||||||||
| DAI5013 | Advanced Computer Vision | 3 | 6 | Major | Master/Doctor | 1-8 | English | Yes | |
| Computer vision is one of the fastest developing fields of artificial intelligence in recent years, and its purpose is to acquire, process, analyze, and understand starting information such as photographs and videos recording the three-dimensional world. In this course, students learn basic concepts and methodologies related to undergraduate computer vision and their applications. Topics covered in this course include image processing and segmentation, feature point detection, optics, image tracking, camera model, 3D reconstruction, and recognition and detection of people and objects. | |||||||||
| DAI5015 | Theories of Convergence Information | 3 | 6 | Major | Master/Doctor | 1-4 | English | Yes | |
| To study deep into digital content, an accurate understanding of “Digital Information” which is the basic unit of digital content is necessary. This course is an introductory course on digital information. This course will introduce various characteristics of digital information, and investigate it in terms of pricing information, digital intellectual property, and so on. | |||||||||
| DAI5016 | Computational Social Science | 3 | 6 | Major | Master/Doctor | 1-8 | - | No | |
| This course deals with various research topics to solve social science problems in a computational way. This course deals with various methodologies such as machine learning, graph theory, and statistics, and learns how each methodology is applied to practical problems. Through reviews of the latest studies, we explore the practice of collecting, analyzing, modeling, and analyzing results of relevant social data for understanding and solving social science problems. | |||||||||
| DAI5017 | Data Science Computing | 3 | 6 | Major | Master/Doctor | 1-8 | Korean | Yes | |
| For graduate students who are not majored in data science, artificial intelligence, this course provides the basic concepts of Python, a programming language for utilizing data science and artificial intelligence, and foster the ability to carry out package and visualization for utilizing artificial intelligence and big data, as well as actual data analysis and applications. | |||||||||
| DAI5018 | Advanced Big Data Analysis | 3 | 6 | Major | Master/Doctor | 1-8 | - | No | |
| Recently, as big data processing and visualization have been activated, research on a methodology for efficiently processing big data has been activated. Examples include federated learning, the use of distributed processing platforms such as Hadoop and Spark. This class aims to develop the basics using the R language suitable for big data processing, and then process and visualize big data as the subject of personal research, implement it on a distributed processing platform, and complete personal thesis. | |||||||||
| DAI5019 | Graph Mining and Learning | 3 | 6 | Major | Master/Doctor | - | No | ||
| Graph is a structure that can represent diverse relations. Social networks, World Wide Web (WWW), power grids, etc., can be represented as graphs. In this lecture, we will first learn how to analyze graphs with various applications. Also, we will learn about graph machine learning that learns graph representations. We will discuss recent applications on graph learning. | |||||||||
| DAI5020 | Emerging Multimedia Applications | 3 | 6 | Major | Master/Doctor | 1-8 | Korean | Yes | |
| This course is designed mainly for master and PhD students. As visible from the course name “Emerging Multimedia Applications”, it will cover the latest research areas of artificial intelligence, computer vision and deep learning for different fields and majors of several departments. The motivation is to help graduate students (MS/PhD) decide their thesis topic because it has been observed that they often feel difficulty at this point. The observation is valid regardless of the availability/unavailability of projects funding to students. (Intelligent Video Summary Generation / Fire Scene Analysis / Violence Recognition and Analysis / Anomaly Detection and Recognition / Movie Data Analysis (Leading Character Recognition, Summarization etc.) / Multi-view Video Data Analytics / Smoke Detection and Segmentation / Multi-Modal Technology for Speech Emotion Recognition / Intelligent Baby Monitoring System / LISTEN Project: Fake Call Detection and Analysis / Action and Activity Recognition / Person Reidentification / Visual Object Tracking / Wireless Capsule Endoscopy) | |||||||||
| DAI5021 | Entertainment Recommendation System | 3 | 6 | Major | Master/Doctor | - | No | ||
| This course provides various methodologies related to recommended systems in entertainment, media, and gaming. It helps algorithmic understanding of various content recommendation technologies and fosters the ability to implement actual recommendation systems through practice. Furthermore, we cover the topics for learning the recent recommendation bias and safe recommendation system model. | |||||||||
| DAI5022 | Entertainment User Experience | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| We address user experience in entertainment services, including games/XR, as well as traditional ICT products. Specifically, it performs learning from a user experience and data privacy perspective within entertainment services. | |||||||||
| DAI5023 | Professional Writing and Communication | 3 | 6 | Major | Master/Doctor | - | No | ||
| This comprehensive hybrid course is designed for master’s and PhD students seeking to elevate their research writing and presentation skills. This course will help students successfully navigate through academic written and spoken language that is used at professional level. Tailored to the field of Computer Science, this 16-week foundation course covers academic writing and presentation skills that will help students’ smooth transition into advanced technical writing that will be the focus of a follow-up course “Advanced Research Writing: From Ideation to Publication”. | |||||||||
| DAI5024 | Advanced Research Writing: From Ideation to Publication | 3 | 6 | Major | Master/Doctor | Korean | Yes | ||
| This comprehensive hybrid course is designed for master’s and PhD students seeking to elevate their technical research writing skills. This course will help students successfully navigate through the publication process. Tailored to the field of Computer Science, this 16-week program covers advanced academic writing, paper crafting, journal selection, submission, revision, presentation skills, and post-acceptance procedure. | |||||||||
| DIM5002 | Metaverse Bigdata Analytics | 3 | 6 | Major | Master/Doctor | Immersive Media Engineering | English | Yes | |
| This course deals with collection, analysis, prediction, and implication retrieval from diverse metaverse data. Basics in data analytics, examining extant studies on metaverse analysis, designing a new study could be included for this course. | |||||||||
| DIM5003 | Immersive Media Seminar 1 | 2 | 4 | Major | Master/Doctor | 1-4 | Immersive Media Engineering | Korean | Yes |
| This course provides core and application technologies of immersive media processing, and discussion will be conducted. Investigation and presentation of state-of-the-art immersive media technologies will be contducted such as video processing, graphics, artificial intelligence (AI), platform, interaction, culture contents, transmedia, digital human & therapeutics, NFT, and XR studio. | |||||||||