For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| DAI4001 | Introduction to AI and Programming | 3 | 6 | Major | Bachelor/Master | Applied Artificial Intelligence | Korean | Yes | |
| For non-Communists who have no knowledge of programming, this course will understand the basic concepts of Python, a programming language for utilizing 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. | |||||||||
| DAI5001 | Fundamentals of Artificial Intelligence | 3 | 6 | Major | Master/Doctor | 1-8 | Applied Artificial Intelligence | - | No |
| Artificial intelligence is a field of research into information processing models that can mimic human intelligence and cognitive functions. As a fundamental problem of artificial intelligence, it deals with theories and fundamental computational problems on the methods of empirical exploration, reasoning, learning and knowledge expression. It deals with logic-based proof of theorem, game theory, intelligent agent, etc., learns the basic principles of neural network, evolutionary computation, and beigean network, and examines areas such as expert system, computer vision, natural language processing, data mining, information search and bioinformatics as examples of its application. | |||||||||
| DAI5002 | Basic Programming for Artificial Intelligence | 3 | 6 | Major | Master/Doctor | 1-8 | Applied Artificial Intelligence | Korean | Yes |
| For non-Communists who have no knowledge of programming, this course will understand the basic concepts of Python, a programming language for utilizing 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. | |||||||||
| DAI5003 | Mathematics for Artificial Intelligence | 3 | 6 | Major | Master/Doctor | 1-8 | Applied Artificial Intelligence | Korean | Yes |
| This subject is a subject that acquires basic mathematics/statistics needed to understand and utilize artificial intelligence for new students entering the artificial intelligence convergence department, and is a statistical foundation for the free use of artificial intelligence in the future. In other words, through this course, students learn the mathematics required to understand machine learning in conjunction with programming. For this purpose, this class will cover essential requirements for machine learning and courses, such as algebra, calculus, linear algebra, and geometry. | |||||||||
| DAI5004 | Advanced Machine Learning and Deep Learning | 3 | 6 | Major | Master/Doctor | 1-8 | Applied Artificial Intelligence | Korean | Yes |
| In this course, you will learn about machine learning, deep learning, and associated optimization techniques, as well as basic neural networks. And the core models of video processing and natural language processing learn about the theory, application and practice of CNN and RNN. | |||||||||
| DAI5005 | Advanced Data Mining | 3 | 6 | Major | Master/Doctor | 1-8 | Applied Artificial Intelligence | - | No |
| Data mining has recently received much attention as a necessary tool for big data analysis. Learning the technology to design and implement advanced data mining algorithms and analytical platforms, especially in artificial intelligence and computer engineering, plays a key role in deriving valuable knowledge in big data and data science. This subject deals with computer science, data science-based advanced technology, algorithms and key platforms for this. It also learns techniques that effectively analyze super-capacity data, super-fast data, etc. | |||||||||
| DAI5006 | Advanced Natural Language Processing | 3 | 6 | Major | Master/Doctor | 1-8 | Applied Artificial Intelligence | - | No |
| In this course, students are required to Implement programs that can manipulate, analyze, and process language data using Python and machine learning & deep learning models. After taking the course, student can - Explain key concepts from NLP and linguistics - Design data structures appropriate for storing natural language data - Understand how deep learning and machine learning algorithms are used for solving NLP problems - Build program for text classification, clustering, and generation using machine learning and deep learning algorithms - Evaluate the performance of NLP techniques | |||||||||
| DAI5007 | Interdisciplinary Service Design Process | 3 | 6 | Major | Master/Doctor | 1-8 | Applied Artificial Intelligence | - | No |
| This class aims to investigate how to build service design procedures with economic/environmental/experimental perspectives toward customer services. Moreover, a set of interactions and stakeholders’ touchpoints are examined. Moreover, team-based projects, which focus on service design procedures, are conducted for presenting customer data analytics, and examining customer experience in the services, based on the understanding on artificial intelligence and data mining (Pre-required class: Introduction to Artificial Intelligence, Advanced Data Mining, Advanced Machine Learning and Deep Learning). | |||||||||
| DAI5008 | Advanced Reinforcement Learning | 3 | 6 | Major | Master/Doctor | 1-8 | Applied Artificial Intelligence | - | 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 | Applied Artificial Intelligence | 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 | Applied Artificial Intelligence | 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 | Applied Artificial Intelligence | 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 | Applied Artificial Intelligence | - | 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 | Applied Artificial Intelligence | 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 | Applied Artificial Intelligence | - | 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. | |||||||||