For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| AAI2021 | Machine Learning for Understanding Humans and Society | 3 | 6 | Major | Bachelor | 2-4 | Applied Artificial Intelligence | English | Yes |
| This course is designed to cultivate integrated competencies that combine data-driven reasoning, machine learning techniques, and critical understanding of human behavior and social phenomena. Aligned with the Human Track of the AI Convergence major, the course explores how machine learning can be applied to analyze individuals, groups, and societal patterns, while emphasizing a human-centered approach to AI. Using R as the primary analytical tool, students learn practical skills in data preprocessing, visualization, model building, and evaluation, all within the context of real-world human and social data. Throughout the semester, students work with datasets related to society, culture, media, digital platforms, and behavioral patterns. They apply key machine learning methods—including regression, classification, clustering, and dimensionality reduction—to investigate how algorithmic models can reveal insights about human actions and social dynamics. Beyond technical skills, the course incorporates discussions on algorithmic bias, fairness, interpretability, and the societal implications of predictive modeling, encouraging students to critically engage with the broader impact of AI systems. Through hands-on projects and iterative data assignments, learners formulate research questions, select appropriate models, interpret outputs, and connect analytical findings to human and social understanding. | |||||||||
| BUS3045 | Business Analytics and Applications | 3 | 6 | Major | Bachelor | 2-4 | Business Administration | Korean,English | Yes |
| This course covers big data mining from the perspective of management. Therefore, the course title is business mining to represent that our main task is focused on the business analytics. In this sense, realms of the topics which this course deals with include, for example, ● AI theories and methods ● Business mining with big data analytics ● AI-based machine learning and deep learning methods ● Big data mining based on huge datasets collected from sharing economies and crowdfunding online companies ● Online review based affective computing by using deep neural networks ● Deep learning based business model development The course format combines lectures, exercises with either WEKA, R or Python. | |||||||||
| CON4015 | Data-Based Quantitative Research Methods | 3 | 3 | Major | Bachelor/Master | Consumer Science | English | Yes | |
| Data-Based Quantitative Research Methods is a methodological course that introduces the core principles of quantitative research and the procedures of data-driven empirical analysis used across the social sciences. The course is designed to help students understand the full process through which quantitative research formulates research questions, organizes and analyzes data, interprets statistical results, and ultimately derives evidence-based conclusions. Students will learn essential concepts in quantitative inquiry, including research design, variable measurement, sampling strategies, and assessments of validity and reliability. Through hands-on work with Stata, they will conduct key stages of empirical analysis such as data cleaning, descriptive statistics, exploratory data analysis, and regression modeling. This practical engagement will enhance their applied research skills. By the end of the course, students will be able to recognize data structures and patterns, interpret analytical outputs, and use empirical evidence to explain social phenomena. The course focuses on building a strong conceptual understanding of quantitative research and developing students’ capacity to apply data effectively across a wide range of social science research contexts. | |||||||||
| ENG2025 | Data Science for Language Analysis | 3 | 6 | Major | Bachelor | English Language and Literature | English | Yes | |
| This course introduces students to key methods and findings in data science for language analysis. We will begin the course by examining motivations for using big data (rather than just intuition) to understand and analyze language, culture and social change. We then introduce students to the key programing language Python and statistical methods/modules used to analyze language and social science data including pandas, numpy, and matplotlib. | |||||||||
| ENG4034 | Introduction to Digital Humanities | 3 | 6 | Major | Bachelor/Master | English Language and Literature | Korean | Yes | |
| In this course, you will explore some digital tools and technologies used in the humanities and study digital projects available in current humanities research. You will learn about the history of digital humanities, data-cleaning, data-visualization and mapping, website-management, and text-mining. The goal of this course is to give you a chance to expose yourself to a variety of possibilities emerging from the convergence between humans and artificial intelligence, developing before and after Generative AI. | |||||||||
| GSP4007 | Artificial Intelligence and Government | 3 | 6 | Major | Bachelor/Master | Public Administration | English | Yes | |
| This course aims to develop practical and analytical competencies for applying artificial intelligence (AI) in public administration and public policy by introducing core AI concepts and technical foundations and examining their applications in government and the public sector. The first half covers fundamental machine learning and deep learning methods-including supervised and unsupervised learning, regularization models (Lasso, Elastic Net), decision trees and ensemble methods (Random Forest), neural networks, recurrent neural networks (RNN), and support vector machines (SVM)-while the second half focuses on empirical studies and policy cases illustrating how these algorithms are used in governmental operations, public services, regulation, policy evaluation, and policy areas such as welfare, labor, and health. Throughout the course, students will engage in discussions on key issues at the intersection of government and AI, including decision-support systems, administrative efficiency, policy targeting, predictive analytics using public data, and concerns related to algorithmic bias and accountability. | |||||||||
| PAD2019 | Strategic Planning and Performance Management | 3 | 6 | Major | Bachelor | 2-3 | Public Administration | English | Yes |
| The course aims to understand the foundation (concepts, models, operational principles) of strategic planning and performance management, develop practical capacity through analyzing various case studies and exploring viable future options, and improve research capacity by investigating the realities/data relating to strategic planning and performance management. | |||||||||
| PAD3020 | Policy Implementation | 3 | 6 | Major | Bachelor | 3-4 | Public Administration | English | Yes |
| A policy implementation studies has the shorter history than a policy making studies. Most people think a policy implementation carries out mechanically. But a policy implementation occupies extensive part of public administration in reality and unexpected situations make the its direction wrong. Therefore a policy implementation studies is very important. The lecture of a policy implementation seeks for below. - It is necessary that practical experiences and studies of policy implementation are reflected policy making. - It is necessary to understand policy implementation's participants - We will investigate various tendencies of theory and case studies to extend our knowledge of policy implementation | |||||||||
| PRS3013 | Public Conflic Management | 3 | 6 | Major | Bachelor | Population Change and Resilience Societies | - | No | |
| This undergraduate course focuses on the theory and practice of conflict management and collaboration for resolving public issues, particularly in the context of complex social problems arising from demographic changes. The course explores methods for resolving conflicts and reaching consensus in public policy development and program implementation processes. Students will enhance their ability to analyze conflicts involving multiple stakeholders and evaluate negotiation and mediation processes. As demographic changes accelerate, the conflicts between various stakeholders around public issues are becoming increasingly complex. This course is designed to strengthen students’ problem-solving capabilities in addressing today's multifaceted challenges by emphasizing the importance of collaboration and negotiation among public, private, and non-profit sectors. The course fosters an understanding that trust-based cooperation and mediation among stakeholders are essential for effective problem-solving in contemporary society. The course recognizes that social conflicts arising from demographic shifts are likely to become more frequent, and it is crucial for public sectors to address these challenges effectively. By integrating insights from various academic fields, this course adopts an interdisciplinary approach to improve problem-solving skills, enabling students to tackle complex social conflicts from multiple perspectives. The goal is to empower students to analyze and resolv | |||||||||
| PSD3007 | Methods and Approaches in Political Science | 3 | 6 | Major | Bachelor | 3-4 | Political Science and Diplomacy | - | No |
| Introduction of various approaches and perspectives in political science and other social sciences is the purpose this class. The class is organized around a number of scholarly examples of current social research and explanation so that the students can recognize the importance of methodology in understanding political phenomena and in doing research projects. | |||||||||
| SOC2003 | Political Sociology | 3 | 6 | Major | Bachelor | 2-3 | Sociology | Korean | Yes |
| This course is primarily concerned with the social bases of political phenomena. In this introductory course, such topics as political power, voting behavior and political movements are discussed in light of several sociological perspectives. | |||||||||
| SOC3046 | Gender and Power | 3 | 6 | Major | Bachelor | 2-5 | Sociology | - | No |
| This course investigates how gender is imbued with power. It will cover topics such as the historical development of feminism, the composition of masculinity and patriarchy, the epistemic implications of studying society from the perspective of women, and the coloniality of gender. The course focuses on theory but also includes specific case studies of gender-related issues in Korea and elsewhere. | |||||||||
| SOC3047 | Qualitative Research Methods & Theory | 3 | 6 | Major | Bachelor | 1-4 | Sociology | English | Yes |
| This course aims to teach students the methodological and theoretical foundations of qualitative and conceptual research in sociology. The course is divided into three sections. Section 1 (“the conceptual”) covers theories in the philosophy of science, different toolkits within philosophical methods, and the meaning of “theory” in sociology. Section 2 (“the field”) teaches how to conduct field research, including interviews and ethnography. This section will include guest lectures from prominent scholars, who will provide students with first-person accounts of conducting fieldwork in challenging social and ethical settings. Section 3 (“text and history”) includes textual and historical methods, such as rhetorical and discourse analysis, historiography, historical causation, and comparative and mixed methods in historical research. The course aims to transfer “insider” information from active researchers about research planning, going through administrative protocols, collecting data, writing, revising, publishing, and facing audience responses. | |||||||||