For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| 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. | |||||||||
| CHS7008 | Strategic Decision-Making with AI | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | Korean | Yes | |
| This course equips students with the essential skills to make strategic decisions using generative AI. As technology rapidly transforms every industry, the ability to critically evaluate AI-generated information and integrate it into decision-making has become a core competency. This course addresses that need by preparing students to work with AI not just as a tool, but as a collaborative partner. Students will gain a foundational understanding of AI systems, particularly the workings of generative AI models. They will learn to analyze unstructured outputs such as text and predictions, assess data reliability, and identify biases. Ethical and responsible use of AI is emphasized to build both technical and social awareness. Going beyond traditional data analysis, the course explores human-AI collaboration in solving real-world problems. Students will examine decision-making case studies across industries including business, healthcare, finance, and policy. Through team-based projects, they will apply AI tools to complex strategic challenges. The curriculum reflects global academic standards, drawing inspiration from courses at MIT, Stanford, and Carnegie Mellon. By aligning with leading institutions, the course helps students build globally competitive capabilities. Ultimately, this course develops future-ready professionals who combine AI fluency with critical thinking and leadership. It is an essential foundation for navigating a world where AI shapes strategy. | |||||||||
| CHS7008 | Strategic Decision-Making with AI | 3 | 6 | Major | Bachelor/Master/Doctor | Challenge Semester | Korean | Yes | |
| This course equips students with the essential skills to make strategic decisions using generative AI. As technology rapidly transforms every industry, the ability to critically evaluate AI-generated information and integrate it into decision-making has become a core competency. This course addresses that need by preparing students to work with AI not just as a tool, but as a collaborative partner. Students will gain a foundational understanding of AI systems, particularly the workings of generative AI models. They will learn to analyze unstructured outputs such as text and predictions, assess data reliability, and identify biases. Ethical and responsible use of AI is emphasized to build both technical and social awareness. Going beyond traditional data analysis, the course explores human-AI collaboration in solving real-world problems. Students will examine decision-making case studies across industries including business, healthcare, finance, and policy. Through team-based projects, they will apply AI tools to complex strategic challenges. The curriculum reflects global academic standards, drawing inspiration from courses at MIT, Stanford, and Carnegie Mellon. By aligning with leading institutions, the course helps students build globally competitive capabilities. Ultimately, this course develops future-ready professionals who combine AI fluency with critical thinking and leadership. It is an essential foundation for navigating a world where AI shapes strategy. | |||||||||
| CLA7101 | AI-Assisted Research Methods for Linguistic Data | 1 | 2 | Major | Bachelor/Master/Doctor | Liberal Art | Korean | Yes | |
| AI-Assisted Research Methods for Linguistic Data is an interdisciplinary course designed for undergraduate and graduate students who wish to conduct research using linguistic data. Through step-by-step, hands-on activities, students engage in the entire research process—from identifying a research topic to collecting and preprocessing data, conducting experiments, visualizing results, and writing an academic paper—with the support of generative AI and a variety of AI-assisted tools. Upon completing the course, students will be able not only to independently carry out the entire process of linguistic data research but also to effectively select and utilize appropriate AI tools at each stage. They will also develop the ability to critically evaluate AI-generated outputs and apply them to their research in an informed, responsible, and independent manner. | |||||||||
| CLA7101 | AI-Assisted Research Methods for Linguistic Data | 1 | 2 | Major | Bachelor/Master/Doctor | Liberal Art | Korean | Yes | |
| AI-Assisted Research Methods for Linguistic Data is an interdisciplinary course designed for undergraduate and graduate students who wish to conduct research using linguistic data. Through step-by-step, hands-on activities, students engage in the entire research process—from identifying a research topic to collecting and preprocessing data, conducting experiments, visualizing results, and writing an academic paper—with the support of generative AI and a variety of AI-assisted tools. Upon completing the course, students will be able not only to independently carry out the entire process of linguistic data research but also to effectively select and utilize appropriate AI tools at each stage. They will also develop the ability to critically evaluate AI-generated outputs and apply them to their research in an informed, responsible, and independent manner. | |||||||||
| COE2001 | Intelligent Information Society and AI Ethics | 3 | 6 | Major | Bachelor | 1-2 | Education | Korean | Yes |
| With the development of artificial intelligence, the information society is entering the intelligent information society. The social benefits brought by artificial intelligence are expected to be substantial. However, recently, ethical issues have arisen in various systems with artificial intelligence installed. In particular, unfairness or reliability issues that overwhelm profits are a threat to the intelligent information society itself. The positive and negative aspects of artificial intelligence are considered and problems are identified. In addition, we will examine the ethical principles and guidelines for artificial intelligence, and consider practical countermeasures through the evaluation of artificial intelligence systems. | |||||||||
| COE2002 | Basic of Generative AI | 3 | 6 | Major | Bachelor | 2-4 | Education | Korean | Yes |
| Due to the recent emergence of Generative AI, the demand for new teaching methods through AI convergence rather than existing theory-oriented education is increasing. Therefore, in this course, we intend to cultivate creative convergence capabilities that can flexibly respond to future industrial and social changes through the core principles of Generative AI and practical application methods. So, we study practical knowledge and application ability of Generative AI core technologies, strengthening problem-solving ability through practice of various tools and algorithms, and how to use convergent AI tools with majors. | |||||||||
| COE2003 | Generative AI Convergence Capstone Project | 3 | 6 | Major | Bachelor | 3-4 | Education | Korean | Yes |
| This course is a hands-on experience of the entire process of a project that uses generative artificial intelligence (AI) technology to solve real problems. Students work in teams to define problems, design and implement solutions to real-life problems using Generative AI technology, and analyze and report the results. Through this comprehensive process, the course goes beyond theory to help students develop practical skills. In addition, through this course, students can develop the ability to apply artificial intelligence theory and algorithms to real problems, and strengthen their collaboration skills, problem solving skills, and communication skills through team projects. | |||||||||
| COE3001 | School Based Experience ＆ Learning I | 2 | 4 | Major | Bachelor | 3-4 | Education | - | No |
| The students of the college of education visit secondary schools and tutor slow learners or help teachers' school works to develop their dispositions for good teachers. | |||||||||
| COE3002 | School Based Experience ＆ Learning II | 3 | 6 | Major | Bachelor | 3-4 | Education | - | No |
| The students of the college of education visit secondary schools and tutor slow learners or help teachers' school works to develop their dispositions for good teachers. | |||||||||
| COE3003 | School Based Experience ＆ Learning III | 4 | 8 | Major | Bachelor | 3-4 | Education | - | No |
| The students of the college of education visit secondary schools and tutor slow learners or help teachers' school works to develop their dispositions for good teachers. | |||||||||
| COE3004 | School Based Experience ＆ Learning IV | 5 | 10 | Major | Bachelor | 3-4 | Education | - | No |
| The students of the college of education visit secondary schools and tutor slow learners or help teachers' school works to develop their dispositions for good teachers. | |||||||||
| COE3005 | Improvement of Teacher’s Spirit and Professionalism | 1 | 2 | Major | Bachelor | 3 | Education | - | No |
| This course is designed for the student teachers who will be the leaders in the future Korean educational system to develop the spirit and the professionalism of teachers. This course is the common major for the undergraduate in education department and cosists of lectures and practicum in educational setting which include guiding students, teaching in real educational setting. | |||||||||
| COE3007 | Startup Field Practice 1 | 3 | 6 | Major | Bachelor | 3-4 | Education | - | No |
| This course is a curriculum that recognizes Startup Activity as a credit.This course is recognized as a credit when it is possible to achieve the learning goal through establishment. Only students who start-up can take classes. Only students who are approved according to the procedures of the school can take courses in the field trips. Be sure to check the requirements and procedures before taking this course. | |||||||||