Korea, South

The major objective of this course is to teach you how to solve problems using algorithmic thinking with the concept of the "object-oriented" programming. We express our algorithms in English, then translate them into the programming language. We cover Python, C++ in this class. During the course, you learn how to use loops, conditionals, functions, arrays, and most importantly "classes." These are the building blocks of programs, which we use to create increasingly complex programs. This course is to understand the fundamentals of object-oriented programming; to understand how to use basic data structures and classes to create complex programs; and to develop problems solving skills by learning algorithmic thinking.

Prerequisite: CSI2100- Computer Programming

This course explores the basic principles of human behavior and how these principles can be applied to product development or design. It also considers how human principles can be combined and applied with engineering principles. At the same time, the content of learning is directly applied by building an efficient, convenient, and safe cognitive system. The goal is to improve psychological scientific analysis ability;  convergence technology capabilities, and the ability to utilize information technology media tools.

The course introduces game theory and its applications in political science to students. Topics include How to Think about Strategic Games, Games with Sequential Moves, Simultaneous-Move Games, Combining Sequential and Simultaneous Moves, Strategic Moves, Uncertainty and Information, The Prisoners' Dilemma and Repeated Games, Collective-Action Games, and Applications to Specific Strategic Situations.

This course covers key Concepts of Hermeneutics: Dialogue, Fusion of Horizons, Crossover, 2nd Person, and Naturalism and Deconstructionism. This course is a survey of the ideas of Husserl, Heidegger, and Gadamer, which make up most of what is known as hermeneutics, or the philosophy of interpretation. 

This course is an undergraduate-level seminar on politics of contemporary China. Understanding politics, economy, society, and their complex relations of our neighbor, People’s Republic of China becomes indispensable for everyone no matter what you study and pursue in this globalized era. In this vein, surveying politics of China would be a priority. We try to systematically (not randomly) analyze and understand those objects through applying some theoretical frameworks of political science such as regime type, political institution, participation, contentious politics, clientelism, developmentalism, nationalism, and interactions between domestic and international politics, to them. More specifically, this course aims at (1) understanding basic political history of contemporary China; (2) theoretically and empirically exposing students to major issues and debates in the study of reform-era Chinese politics and helping students understand major characteristics of the Chinese Communist Party regime; (3) In addition to the conventional contents of “Chinese Politics” course, letting students do a “problem-solving” project from creative and multi-disciplinary perspectives of political interactions as well as politics of things; (4) and finally, encouraging students to pursue their own agendas related to contemporary China in further studies in schools and job market (and beyond).

This course is designed to delve into the world of early childhood curriculum, exploring its definition, philosophical and theoretical foundations, and practical implementation. Throughout the semester, students develop knowledge and skills in planning and interpreting curriculum, observing classroom practices, and understanding teacher roles. In addition, students gain deeper understanding of various early childhood curriculum models as well as current trends in the field. The goal is to understand the concept of early childhood curriculum and its core components; to understand how philosophical and theoretical backgrounds are associated with early childhood curriculum; to develop skills in planning, developing, and implementing early childhood curriculum; and to analyze current trends and the future of early childhood curriculum.

Prerequisites: majoring in Child and Family Studies

This course is a course to study the theory and practice of computer graphics. In theory, we study graphics algorithms and mathematical fundamentals, and also learn programming to apply them in practice. Key topics include math for graphics, Transformation, Viewing, Texture mapping, Lighting, Using models, Advanced buffer techniques, Advanced rendering and animation techniques, etc. The programming language used is C++, and the class is conducted using the OpenGL API.

Prerequisites: C/C++ language programming, object-oriented programming, data structures, and differential calculus.

This course provides a general introduction to computer vision. Major topics include image processing, detection and recognition, geometry, video analysis, and deep learning. Students learn basic concepts of computer vision as well as hands on experience to solve real-life vision problems. Students learn basic algorithms of computer vision, learn deep learning based computer vision algorithms, and apply learned methods for practical applications.

Prerequisites: Calculus, Linear algebra, Probability

Have you heard of Big Data or AI? What about Data Science? Data Science is the field of study that deals with data acquisition, data analysis, and decision making with domain knowledge. In the discipline of Data Science, data refer to either structured or unstructured data, which is commonly referred to as Big Data. Tools for analyzing Big Data in Data Science are called machine learning that is a sub-field of Statistics, and machine learning is known as a workhorse of AI. This mathematical statistics course is designed to provide a comprehensive introduction to the mathematical study of statistics (or machine learning). Without the knowledge of mathematical statistics, you cannot fully understand machine learning algorithms including Deep Learning. Topics include probability, random variables, univariate or multivariate distributions, elementary statistical inference, and limiting distributions. Emphasis is on the theoretical development and practical implementation of each topic, including definitions, theorems, proofs, computer programming, and simulations.

Prerequisites: STA1001. Introduction to Statistics (or equivalent course), STA1002. Calculus (or equivalent course)

Students learn about the basic concepts of electric circuits including; circuit elements, Kirchhoff’s law, basic RLC circuits, circuit theorems, Op Amp, sinusoidal steady-state analysis, frequency response and Laplace transform. Topics include Electric circuit variables, Circuit Elements, Simple Resistive Circuits, Techniques of Circuit Analysis, The Operational Amplifier, Inductance, Capacitance, and Mutual Inductance, Response of First-Order RL and RC Circuits, Natural and Step Responses of RLC Circuits, Sinusoidal Steady-State Analysis, and Sinusoidal Steady-State Power Calculations.

Prerequisites: Engineering mathematics, Differential Equations