Korea, South

This course is an overview of marine environments, organisms, and ecosystems. Students explore the physical, chemical, and biological characteristics of the ocean, emphasizing major marine ecosystems (coastal, pelagic, polar/subpolar). The course also examines how human activities affect marine ecosystems and discusses possible conservation strategies. 

This course provides a step-by-step approach to tackle any personal, professional, or world issue imaginable. Learn techniques to clearly define problems, research solutions, weigh options, and implement plans. Gain the skills to transition from panic to possibility. This course takes an interactive, hands-on approach to building problem-solving skills. Through case studies, team projects, and simulations, students learn and practice key frameworks including defining problems, researching context and analyzing root causes, brainstorming creative solutions, evaluating options, planning implementation, and communicating and collaborating. The course provides abundant opportunities to apply problem-solving techniques to real-world issues. Students develop critical thinking, teamwork, communication, and creativity skills to become decisive, strategic problem solvers.

This course examines Existentialism and Phenomenology in terms of their unique and considerable contributions to the Western, and particularly French, aesthetic tradition. Students examine views on art by some of the best-known modern theorists to gain understanding of the philosophical issues motivating French aesthetic thought at the end of the 19th and beginning of the 20th Centuries. The course then covers a shift from a broadly existentialist view of literature to one influenced by the growing structuralist movement and reviews philosophical investigations of the arts in relation to theories of perception.  

This course focuses on applying linguistic theories to real-world contexts, examining the intricate connections between linguistic and non-linguistic phenomena. By analyzing these relationships at individual, societal, and global levels, students will explore how linguistic theories are utilized to understand and address complex issues, gaining insights into their practical relevance and broader impact. Students examine the evolution of language and linguistics, with emphasis on the processes of language development and decline. Students also apply a linguistic perspective to everyday contexts, including education, language policy, K-pop, and culture. 

This special topics data sciences course covers up-to-date research trends in prompt engineering and prompt engineering interactions with large scale language modeling. The course examines how prompt engineering significantly impacts the effectiveness of LLM-based applications and interactions with generative AI. 

Academic researchers, industry vendors, and practitioners have proposed many practical techniques and guidelines for building LLMs or applications on LLMs. In this course, students review concepts and techniques that can be used to guide the model in how to behave in a way that is aligned with users' preferences or perform a specific task. 

Topics include basic concepts of LLMs, Foundation model vs custom model, Fine tuning vs prompt tuning, Methods of prompt engineering, Agentic workflow, Integrating local preparatory knowledge bases, and more. 

This course introduces an overview of the cultural tradition of East Asia by examining classical Chinese narratives translated into English. It explores how these narratives depict the essence of humanity and the world, discussing their influence on modern East Asian culture. Through the course, students identify the cultural characteristics inherent in East Asian civilization and develop a critical understanding of its contemporary discourses. 

Student will be able to: 1. Understand the cultural concepts that underlie the individual, the family, and the state in East Asia 2. Learn the historical development of China, Japan, and Korea and their relationships with each other 3. Practice reading East Asian texts in their own literary tradition and relating them to cultural contexts 

This course covers basic concepts in real estate finance, including basic concepts in mortgages, time value of money, income producing property taxes, and real estate investment and accounting issues. In addition, this course covers current issues in real estate finance, such as household debt or sub-prime crisis in the US. At the end of this lecture, the course briefly introduces how to manage micro-level data and calculate some statistical moments. Topics include Mortgage loan foundation: The time value of money, Fixed interest rate mortgage loan, Adjustable and floating rate mortgage loans, Mortgages: Additional concepts, analysis, and applications, Single-family housing: Pricing, Investment, and tax consideration, Underwriting and financing residential properties, Understand a toy mortgage default model (one-sided limited commitment model), Income-producing properties: Leases, rents, and the market for space, Investment analysis and taxation of income properties, Financial leverage and financing alternatives, and Risk analysis. 

Prerequisite: Macroeconomics, financial economics, econometric, and economic mathematics are recommended. 

This course theoretically examines the macroscopic role that entrepreneurs and entrepreneurship play in the market economy and examines management theories about individual and organizational-level phenomena that affect entrepreneurship, for example via management case studies. The scope of this class is not a simple livelihood-type entrepreneurship, but opportunity-capturing entrepreneurship that creates new market value. Topics include History of the Startup Ecosystem in Korea, Entrepreneurship vs Management, Opportunity recognition, Numbers and Venture Capitalists, Business Model and Competitor Analysis, Consumer Behavior, Business Models Topology and Big Data, and more. 

This course explores the underlying principles of several cutting-edge topics in machine learning and deep learning, including adversarial attacks, deep metric learning, generative models, information theory, and reinforcement learning.  

In addition, the course examines the end-to-end construction of modern large language models and practices core concepts by implementing them. Students engage in coding assignments and team projects using GPU-enabled computer servers to test original ideas. 

Topics include concepts and history of deep learning, backpropagation techniques such as stochastic gradient descent, initialization techniques, regularization techniques such as drop out, convolutional neural networks (CNN), CNN architectures, visualization of CNN, recurrent neural networks (RNN), RNN applications, and other applications including reinforced learning. 

To emphasize practical skills to implement deep learning algorithms, programming-related lectures and lab sessions are included. The most important/popular language, Python, will be covered and a Python math library called Numpy is also taught with lab sessions. Advanced deep learning algorithms are implemented in Tensorflow library, which is introduced as well including relevant lab sessions 

This course covers various topics in probability theory and introductory random processes such as probability, random variables, expectations, characteristic functions, random vectors, random processes, correlation functions, and power spectrum. A number of engineering examples are examined for students’ better understanding of principles.