Yonsei University

In modern society, where uncertainty is increasing, the importance and necessity of intimate relationships—such as romantic partnerships, marriage, and family—are being increasingly emphasized. In particular, phenomena related to love, marriage, and family are changing more rapidly than ever before. A broad examination and understanding of these intimate relationships not only help individuals respond flexibly to such changes, but also contribute to the formation of healthy values regarding love, marriage, and family. Ultimately, this fosters individual happiness and promotes the well-being of families and society as a whole.

This course introduces the basic theories, design, and evaluation techniques required in future architectural practice, focusing on thermal environmental factors.   

The field of architectural environment refers to the technical area that deals with the physical performance of buildings, which must be considered throughout the process of producing architectural structures. The physical performance of a building depends on the spatial elements, thermal/light/sound environment factors, indoor air quality factors, and the architect's knowledge and experience related to the integration of these elements. 

The course prepares students to create comfortable indoor environments, as well as to design environmentally friendly and energy-efficient buildings. This course covers architectural sustainability, environmental control and passive design in architecture, and the basic principles and performance evaluation methods for building environmental systems: heating, cooling, lighting, and energy. 

Water management engineering includes infrastructures and management for water cycle in natural and engineered environments.  

This course covers fundamental knowledge about water infrastructure engineering for natural water cycle and engineered water cycle with emphases on the effects of climate change and urbanization on natural water cycle, and urban water supply and wastewater sanitation.  

In addition to fundamental knowledge, students use principles, mathematical equations, and machine learning to solve water infrastructure problems. This course is intended for 3rd year undergraduate students of Civil and Environmental Engineering or similar. 

Prerequisite: Environmental Engineering and Lab course in CEE or similar department. . Assessments: Midterm exam (30%), final exam (30%), team project (15%), homework (15%), participation (10%).

This course focuses on topics related to the processes and functions carried out during the lifetime of a cell. Topics including the actin and microtubule cytoskeletons as well as molecular motor proteins and cell motility are covered in detail. We also focus on cell-cell communication, signal transduction and cell signaling in the context of unicellular and multicellular organisms. In addition, we spend time discussing the cell cycle with an emphasis on the regulation of transitions between cell cycle stages.

Each process covered in class plays a role in some important aspect of cell physiology and we touch on examples of defects in these systems that can lead to disease. Each topic includes discussions of experimental strategies and laboratory techniques.

Prerequisites: General Chemistry (at least 1 semester), General Biology (at least 1 semester), Biochemistry I

This course introduces one interpretive key to the understanding of modernity and its relationship with postmodernity: the cultural process of secularization and the mental and social changes that secularization brought with it. 

The course searches for deeper insight on our contemporary world and examines the necessary elements to judge some of its cultural trends.  

Students conduct independent research on folklore in addition to reading works of modern literature, and consider how myth and religion continue to affect the ways modern people engage in political activity as well as influence their understanding of how the world works. Students also explore what stories are the most meaningful in their lives or in the lives of their friends and contemporaries. 

Personnel Economics studies the economics of the workplace using simple but formal economic models. Models of employee motivation, compensation, and selection are melded with real-world examples and with field studies of actual workplaces. Personnel economics takes an economic approach to the two key problems of human resource management (HRM): employee selection and employee motivation. The course approach combines elements of microeconomic theory, behavioral economics, and evidence from lab, field, and natural experiments. Familiarity with intermediate microeconomic theory such as budget constraints and indifference curves is presupposed. Familiarity with basic probability and regression analysis is helpful but not essential. 

This course introduces machine learning and deep learning, which are the most widely used methods for implementing artificial intelligence systems. It also covers a broad range of foundational topics to help students understand machine learning and deep learning systems, making the course accessible to students of all majors.  

This course is intended for students with no background in AI or deep learning. Thus, the topics are broad and on an introductory level. Topics include Deep Learning, Linear Algebra Fundamentals, Artificial Intelligence Basics, Machine Learning Fundamentals, Neural Network Basics, Deep Learning Fundamentals, Optimization, Convolutional neural networks, Recurrent Neural Networks, Latest Deep Learning Topics as time allows. 

Prerequisite: Linear Algebra 

This course explores the fundamental structure and design principles of computer systems. It covers key topics such as computer abstraction and technology, instruction set architecture, arithmetic for computers, processor design, memory hierarchy, and parallel processing. Special emphasis is placed on understanding modern computer architecture trends, high-performance computing, and AI accelerators. By the end of this course, students gain a deep understanding of the interaction between hardware and software and develop essential skills for performance optimization.

This course investigates how language shapes communication, organizes interaction, and builds community in online game cultures, with particular attention to two popular Korean games: MapleStory (MMORPG) and League of Legends (MOBA).  

Please note that students are expected to demonstrate a clear interest in acquiring gameplay proficiency in these games and must be willing to participate in structured, designated group play sessions. This course is not recommended for students without prior gaming experience. 

The first half of the semester focuses on MapleStory alongside individual assignments and a midterm, while the second half pivots to structured League of Legends team play and group-based projects.  

Through lectures, assigned readings, fieldwork in PC bangs, and collaboration with Gen.G’s GGX facility, students analyze how game genres, platforms, and play spaces structure linguistic practices, social norms, and player identities.  

By the end of the course, students are able to: analyze how language functions in online games (commands, politeness, toxicity, role talk, jargon) using basic tools from pragmatics and discourse analysis; compare MapleStory and League of Legends as distinct “linguistic ecologies,” showing how genre and tempo shape communication; conduct small-scale empirical studies of game-related communication (in-game chat, voice, Discord, PC-bang interaction, esports events); reflect critically on PC-bang and esports spaces, connecting them to broader debates about youth, stigma, and digital culture in Korea; and work collaboratively in teams to gather, interpret, and present language data from League of Legends. 

This course provides an introductory overview of probability theory, presented in a mathematically rigorous manner. Starting from the definitions of events, random variables, independence, and expectation, we also cover some basic applications such as weak convergence, the law of large numbers, characteristic functions, the central limit theorem, etc. 

Prerequisites: Elementary level of calculus (required), analysis (required), and linear algebra (optional).