강의

2025.9 eClass 참조하세요.

2025.9 TU-WBI. 현장전문가 특강, 협동학습. eClass 참조하세요.

2025.3 블렌디드 러닝. eClass 참조하세요.

2023.9. Socio-economic Complex Adaptive System: Agent-based Modeling, Seoul National University (4.48/5)

2024.3. Socio-economic Complex Adaptive System: Agent-based Modeling - Foundation, Seoul National University (4.64/5)

2024.9. Socio-economic Complex Adaptive System: Agent-based Modeling - Simulation Project, Seoul National University (4.78/5)

Participants will learn about concepts applied in agent-based modeling and simulation techniques, complex network modeling, and learning processes within networks. The course begins with fundamentals of agent-based modeling (i.e., analysis, design, and simulation). It introduces notable networks and adequate network measures to capture their growth dynamics. Then, we focus on learning and knowledge exchange within networks. It also demonstrates how those networks can be investigated and examined in different contexts, such as learning within an organizational structure, strategic interactions, and network dynamics. This course will also teach students how to develop and apply programming skills to raised research questions during lectures.

2023.9. AI BigData Platform, Kyunghee University 

2024.3. AI BigData Platform, Kyunghee University

2024.9. AI DataScience, Kyunghee University

This course is an applied data science course where you will gain a deeper understanding of data literacy to develop AI-powered data problem-solving skills and learn how to apply them to systematic existing literature research cases.  This course is guided by the following teaching principles. 

a. Understand the fundamental principles of data science and stick to the basics.

b. Cover the entire data science lifecycle.

c. Define a systematic literature review problem and take the initiative to practice the concepts you have learned based on systematic studies of existing literature. 

d. Utilize both computational and reasoning thinking.