Seoul National University

This course cultivates entrepreneurship through understanding the current status and trends of the semiconductor industry and the experiences of company founders. In the class, students meet representatives of recently established semiconductor companies, hear about the startup motivation, business model, and future prospects, and share understanding of the overall semiconductor industry and various experiences related to technology-based startups through a Q&A session with the semiconductor CEO. 

This course covers estimating relationships between economic variables associated with agricultural situations. Students are enabled to understand the general concepts about model identification, estimation, forecasting, and policy analysis. Students learn simple regression, multiple regression, and time series analysis. Prerequisite: Principles of Economy, Statistics, Mathematics for Economic Analysis. 

This class is designed for international students studying at SNU, in particular those students who may not have had the opportunity yet to study the language or culture of Korea. It provides a general introduction to the Korean language and important aspects of Korean culture, both traditional and modern. Topics include an outline of the Korean language with honorific forms, Korean history, nature, economy, and society. The course also covers Korean art, music, literature and philosophy as well as problems concerning the traditional culture such as family, relatives, wedding, funeral ceremony, folk's belief, shamanism, seasonal rite and customs. The class is conducted in English, including all instruction, discussion, and assignments. 

This course focuses on the food industry and studies the success and failure cases of marketing and information management in fields such as agriculture, food service, bio industry, and distribution industry, and discusses how to apply them for the development of our food industry. Through case analysis, students will acquire various practical knowledge on how business activities in these industries are developed from the perspective of marketing and information management, and how to solve problems using methods and frameworks. Students who successfully complete this course will have basic skills as management consultants in the field of food and bio business. 

This course introduces population geography to undergraduate students and focuses on the causes and consequences of population change. It enables students to understand demographic dynamics brought about by birth, death, and mobility. The course examines the tension between how demographic knowledge (and in particular, demographic categories) has been constructed and how such categories are used. The course pays special attention to the spatial mobility of human beings as the increase in human mobility receives increasing attention from both academia and policy-making. 

This course covers the concepts, paradigms, and explanations needed to become effective practitioners in culturally, racially, and linguistically diverse classrooms and schools. An important of goal of this course is to help future educators attain a sophisticated understanding of the concept of culture and to view race/ethnicity, gender, and class as interacting concepts rather than as separate and distinct. As a result, intersectionality, i.e., how race/ethnicity, gender and class are fluid variables that interact in complex ways is an overarching concept in this course. In doing so, the course integrates the content of Sustainable Development Goals (SDGs) to provide students an opportunity to explore issues of inequalities and injustices related to race/ethnicity, gender, and class within their communities from a global perspective.  

The course collaborates with National Taiwan Normal University (NTNU) through online interactions and Project-Based Learning (PBL) to facilitate participants’ understanding of local issues and current circumstances pertaining to race/ethnicity, gender, and social class in South Korea and Taiwan. Through PBL focusing on student-selected topics, participants from both societies will actively engage in intercultural collaboration and knowledge exchange, promoting social inclusivity and advancing SDGs grounded in principles of multicultural education and sustainable development. 

This course covers programming using data programming language on an introductory yet rigorous basis for highly motivated students with little or no prior experience in programming. The course focuses on collecting and analyzing data, as well as the grammar of the data programming language and provides an in-depth look at big data analysis.  

Modern scientific, engineering, and business applications are increasingly dependent on data, yet traditional data analysis technologies were not designed for the complexity of big data. Big data analysis has emerged as a new, exciting, and fast-paced discipline that explores novel statistical and implementation challenges that emerge in collecting, processing, storing, and extracting knowledge from big data.  

Students learn how to collect, process, and analyze large amounts of data by combining data analysis technology and artificial intelligence technology.  Students will use Python as a powerful tool for data management and analysis and analyze structured and unstructured data using LLMs for natural language processing, text analysis, and graph-based multi-agent systems.  In addition, data management and system design techniques using RAG (Retrieval-Augmented Page 1 of 9 Generation) and APIs that support prompt engineering techniques and AI-based decision-making will also be covered. 

This is a useful course for students who want to combine and utilize data analysis and artificial intelligence technology in various fields such as information technology (IT), business analytics, marketing, and strategic planning. 

Prerequisites:  Basic knowledge of the system configuration of the operating system (Windows, macOS, etc.) (e.g., setting environment variables, etc.).  Basic knowledge of the Python programming language 

This advanced topics course covers reinforcement learning, search, and test-time scaling of large language models that are expected to drive the next generation of AI systems. 

Topics include: Basics of RL (Markov Decision Process and Policy evaluation), Basics RL (Imitation learning, Deep policy gradient methods), Basics of RL (Deep Q-Learning, Rainbow DQN); Symmetric alternating Markov games, Monte Carlo tree search, expert iteration, and AlphaGo; Imperfect information games, Counerfactural regret minimization, and Pluribus; NLP basics (RNN, beam search, tokenizers); NLP basics (Transformers, encoder-decoder architectures); Instruction fine-tuning, Scaling laws of LLM pre-training; Reinforcement learning with human feedback, direct policy optimization, Group Relative Policy Optimization (GRPO); Chain of thought, Process reward models, Prover-verifier games; In-context learning, Scaling LLM Test-Time Compute; DeepSeek-R1. 

This covers how international disputes are settled (or not) under international law. The class focuses on international disputes and examines how international law is applied to legal issues of disputes. Students obtain a critical approach to international law in perspective of its role and limits. This course also examines other mechanisms of dispute settlement developed in specific areas of international law. There are no prerequisites, and no prior knowledge in international law will be assumed. This course is primarily for students who have not studied international law before. Students with different backgrounds in international law are also welcome in this course. 

This course provides students with an opportunity to explore various actual cross-border M&A (merger and acquisition) transactions including outbound and in-bound investments and related contracts and processes from a practitioner’s perspective. 

Under the guidance of professors or lawyers at legal clinics or legal counseling centers on campus or at law offices off campus, students gain experience through participation in planning, due diligence, contract drafting and negotiation exercises. The course allows students to experience the practical aspects of working on cross-border M&A transactions and to equip them with the ability to spot potential issues and come up with solutions in the context of such transactions, thereby helping to prepare them for a future career as an international corporate practitioner. The course is conducted in English, with an emphasis on enhancing the students’ ability to communicate in English and handle English language documents, which are critically important skills for engaging in international transactional work.