My primary teaching expertise is data analytics, covering a wide range of topics, including machine learning, econometrics, database management, and programming for data science. I have taught relevant courses since 2021 and was a teaching assistant for other relevant courses between 2016 and 2022. In addition to rich experience in teaching data analytics and programming, I enrich my courses uniquely based on practical and theoretical insights from my research and collaboration with industries. I am also interested in developing and teaching new courses, including (but not limited to) AI Governance and Ethics, Data Science for Social Good, Generative AI and Programming, and Machine Learning for Causal Inference.

University of Connecticut

[Master's] OPIM 5671: Data Mining and Time Series Forecasting

• Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2025
• This course discusses data mining techniques that can be utilized to analyze large-scale operational data and extract actionable information and knowledge (meaningful patterns, trends, and anomalies) to help make decisions. It will focus on text mining (or natural language processing) and time series forecasting that can be applied to various business domains, such as digital marketing, supply chain management, corporate finance, and asset pricing.

[Master's] OPIM 5512: Data Science Using Python

• Spring 2023, Spring 2024, Spring 2025
• In this course, students will learn the basics of Python programming and implement advanced data science techniques based on the programming skills. With the assumption that students have concrete prior knowledge of basic data analytics but not technical familiarity with Python, this course introduces the details of Python libraries, the syntax structure and meaning, and application tips. Conceptually, it focuses on predictive analysis for real-world datasets using a wide range of methods covering linear regression, deep learning, tree-based models, and reinforcement learning.

KoreaTech

[Undergraduate] Management Database and Applications

• Fall 2021
• This course aims to provide a foundational understanding of database concepts and practical skills for using databases. Students will learn about the fundamental theories of database design, Structured Query Language (SQL) and how to apply these concepts through hands-on practice. The course includes designing and building databases using MS Access to simulate real-world applications. By the end of the course, students will develop basic information processing skills necessary to utilize data and databases in business contexts effectively.

Guest Lectures

• "Data Visualization," KDI School of Public Policy and Management, July 2022
• "Basic Statistics and R Programming," KAIST Graduate School of Green Growth, August 2021
• "Digital Streaming, Entertainment, and Business Analytics," HKUST Business School, May 2021