Korea, South

This entry-level course covers statistical analysis related to survey methodologies and statistical analysis tools such as R, Stata, and Python for data analysis as a general topic of international studies.  

Students learn various data analysis methodologies in the fields of international economy, international development cooperation, and international relations, and how to generate, interpret, and critically judge quantitative analysis results on major topics covered in those fields. 

This course is ideal for undergraduate students in international studies who want to apply econometric principles to real world data. It is particularly suited for those seeking to develop skills in R programming, including data cleaning, visualization, statistical modeling, and interpretation, to support independent research and future academic or professional endeavors. 

This course explores users as humans who are changing/expanding in the AI era, exploring the limitations of recent AI services, and then designing user-centered AI services. Students learn methods to understand users, and then define user interfaces and their interaction. Prototyping techniques and evaluation methods are also provided. Service design is carried out at the level of expressing ideas, not at the level of actual driving. 

In particular, this class is conducted with a focus on practice rather than lecture-style delivery, and coaching for each process customized for each team is carried out through close interviews and discussions. In addition, the course benchmarks related services in depth from the perspective of actual business to identify limitations and opportunity points and carry out a process to turn them into deliverable results. There are no special technical/technical prerequisites required for this course, however, students must be proactive and enthusiastic about participating. 

This course surveys and introduces topics vital to understanding our planet.  

The Earth is composed of four major systems, such as geosphere, hydrosphere, atmosphere and biosphere, which govern the surface processes and internal dynamics of the Earth. This course explores Earth processes of crustal evolution, environmental changes, and biotic successions since its formation as a planet.  

This course introduces the basics of business analytics, which uses data and models to make business decisions. It focuses on descriptive analytics and predictive analytics, and covers detailed topics such as data management, data visualization and summary, hypothesis testing, linear regression models, logistic regression models, decision trees, and data mining. The goal of this course is for students to 1) identify key factors in business decisions, 2) apply various tools and techniques to make evidence-based business decisions, and 3) effectively explain and communicate those decisions to various audiences and stakeholders. 

This course explores issues of economic development in a globalizing world. Today, trade policy is at the forefront of the development agenda, and it is a critical element of any strategy to fight against poverty. This renewed interest in trade liberalization does not come from dogma, but instead is based on a careful assessment of development experience over the last 50 years. This course examines how multilateral trade cooperation in the World Trade 2 Organization (WTO) helps developing countries create and strengthen institutions and regulatory regimes that will enhance the gains from trade and integration into the global economy. The course also surveys how the growth of regional trading blocs affects developing countries that are turning to regionalism as a tool for economic development. 

Prerequisite: Principles of International Commerce (Highly Recommended).

This course covers the technical foundations of photography and the unique aesthetic experiences it offers, incorporating aspects of photographic philosophy, media aesthetics, and the use of AI generators in various projects. Topics also include innovative photo projects utilizing AI generators and keeping pace with evolving media trends. Through this exploration, students examine the linguistic value and role of photography across fields such as research and business. 

This survey course covers the history of the Chinese Communist Party and the People’s Republic of China. It covers the pre-1949 revolutionary struggles, socialist transformation and construction in the 1950s, political movements from the late 1950s to the late 1970s, and post-Mao economic and political reforms, up to the consolidation of Xi Jinping’s personal rule. The permeation of the party-state’s power into diverse aspects of social life is one key feature of communist rule, and this entire course closely integrates national and international political events with the daily lives of Chinese people. It examines historical transformations in the fields of economics, culture and the arts, family and gender relations, public health, and environment and ecology during the century, throughout the study of revolutionary wars, political movements, and reforms. 

This course focuses on learning how to structure and solve complex decision problems and analyzing their property and solutions quantitatively. It covers advanced theories, algorithms, and applications of management science in the context of quantitative decision modeling and optimization. Topics include the theory and applications of linear, nonlinear, integer programming, as well as advanced modeling approaches to optimization problems under various sources of uncertainty. Students will also explore recent advances in the field, including integration with machine learning, and address real-world decision challenges across various domains, ranging from finance, marketing, and production to healthcare, sports management, and humanitarian operations. The course involves hands-on learning using relevant languages (e.g., Excel, Python) and state-of-the-art solvers. A basic understanding of mathematical optimization and probability is required. 

This course empowers undergraduate students in the College of Natural Sciences with essential knowledge in programming and artificial intelligence. Regardless of their specific majors, students gain foundational insights into computer science, computational science, statistics, and deep neural networks. This course equips students with practical skills that can be directly applied to scientific challenges. Through a combination of theory and practical exercises, this course offers students the opportunity to tackle real-world problems and work with data using artificial intelligence techniques. Students who possess basic computing and programming skills gain an understanding of how artificial intelligence and programming are applied in various subfields of natural sciences, fostering their ability to utilize these skills in future research endeavors. 

This introductory course covers mathematical topics closely related to computer science. Topics include: logic, sets, functions, relations, countability, combinatorics, proof techniques, mathematical induction, recursion, recurrence relations, graph theory, and number theory. The course emphasizes the context and applications of these concepts within computer science. Prerequisites: No prior programming experience is assumed.