Seoul National University

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 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. 

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 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 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.