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Teaching Experience

Instructor:

​BUAN B493: Programming Fundamentals for Data Analysis

  • Spring 2026, Class size: 10

This course introduces students to the fundamentals of programming with a strong emphasis on data analysis and problem-solving. Using Python as the primary language and Visual Studio Code (VS Code) as the integrated development environment, students will learn how to write, debug, and document programs that manipulate, analyze, and summarize data. The course follows a fundamentals-first approach, emphasizing computational thinking, structured programming, and reproducible analytical workflows relevant to business, economics, social sciences, and applied analytics.

Instructor:

​BUAN B205: Business Analytics with AI

  • Spring 2026, Class size: 32 & 21 (two sessions) 

Business Analytics with AI is a hands-on, applied course that prepares students to make data-driven business decisions by combining foundational statistical methods with modern artificial intelligence tools. Students learn to analyze and interpret business data using techniques such as data visualization, hypothesis testing, regression analysis, and predictive modeling. The course emphasizes real-world applications through data storytelling, analytical problem-solving, and decision support. Students work with industry-relevant tools including Excel, Google Sheets, and Python, alongside Generative AI platforms such as ChatGPT, Gemini, and Perplexity to enhance efficiency, insight generation, and interpretation. By integrating classical analytics with AI-powered technologies, the course equips students with the analytical agility, technical confidence, and strategic mindset needed to succeed in today’s data-driven and AI-enabled business environment.

Instructor:

​BUAN B100: AI and the Future of Business

  • Fall 2025, Class size: 32 & 21 (two sessions) 

AI and the Future of Business introduces students to the structure, dynamics, and complexities of modern business in an increasingly digital and AI-driven global environment. The course examines how artificial intelligence, data, and emerging technologies are transforming organizational strategy, culture, markets, and decision-making. Topics include ethical and socially responsible use of AI, global business environments, innovation and entrepreneurship, management, marketing, accounting, and finance, with an emphasis on how AI reshapes business models, competitive advantage, and workforce dynamics. Through real-world examples and applied analysis, students develop a strategic understanding of how businesses leverage AI to drive innovation, efficiency, and sustainable growth in a rapidly evolving economy.

Instructor:

​BUAN T194: Telling Stories with Data

  • Fall 2025, Class size: 26 & 25 (two sessions) 

  • Spring 2026 Class 26

This course focuses on transforming raw data into compelling, insightful narratives. Students will learn how to effectively communicate complex information using data-driven storytelling techniques that combine statistical analysis, data visualization, and narrative strategy. The course emphasizes clarity, context, and audience engagement, teaching students to use data not just to inform but to persuade and inspire action. Additionally, this course will equip students with practical skills to interpret, summarize, and explain both qualitative and quantitative data. Through hands-on projects, students will practice using tools such as Excel and Tableau for visualization, and will critique real-world examples from journalism, business, public health, and policy. By the end of the course, students will be able to craft stories that make data meaningful and accessible to diverse audiences.

Instructor:

​AAEC 2305: Fundamentals of Agricultural and Applied Economics (Microeconomics)

  • Fall 2023, Class size: 35

  • Spring 2024, Class size: 44

  • Fall 2024, Class size: 54

This course introduces students to the application of microeconomics to real-world problems. It is an introductory course in microeconomics and assumes no prior knowledge of economics. The objective is to introduce students to essential concepts in microeconomics, basic demand and supply analysis techniques, and the economic framework for policy analysis. Course topics include demand, supply, market equilibrium, elasticities, consumer choice, production and cost, perfect competition, monopoly, monopolistic competition, oligopoly, government action in markets, taxes, market efficiency, consumer/producer surplus and externalities.

Teaching Assistant: ​

ECO 5414: Econometrics (Ph.D. class)

  • Spring 2022, Class size: 12

This course is a Ph.D class that teaches fundamental knowledge of applied econometrics, with a focus on the relationships between economic variables. It exposes students to hypothesis testing and the economic interpretation of statistical results. Key areas covered include simple and multiple regression analysis, hypothesis testing, heteroskedasticity, and serial correlation. These strategies are used to real-world data, aiming for policy analysis across areas.

Teaching Assistant: ​

ECO 4305: Introduction to Econometrics

  • Spring 2022, Class size: 40

This undergraduate course covers the fundamentals of econometrics, emphasizing the application of economic theory, statistics, and mathematical tools to analyze economic relationships. Topics addressed include ordinary least squares and simple regression analysis, hypothesis testing, and heteroskedasticity.

Teaching Assistant:

​​ECO 4322 – The Economics of Labor Markets

  • Spring 2022, Class size: 45

This course introduces student to the operations and economics of labor market. its covers various areas and topic including Labor as a factor of production, labor market participation and hours worked, compensating wage differentials, human capital investment, income inequality, migration, and discrimination.

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