Teaching

A mixed-methods undergraduate course on studying and researching visual culture in contemporary media environments, combining qualitative interpretation, content analysis, and artificial intelligence and machine learning methods including image feature extraction, classification, clustering, and the use of large language models for visual annotation.

A course introducing coding for communication research and professional practice using R, with an emphasis on understanding code, verifying results, and communicating computational findings responsibly.

A graduate course covering principles and practices of data visualization, with a focus on theory, tools, and best practices for communicating data insights effectively.

A hands-on graduate course introducing social media data collection, text and network analysis, visualization, and ethical analytics with Python.

A graduate course on computational text analysis methods for social science research, covering topic modeling, word embeddings, sentiment analysis, and large language models.

An undergraduate course on data-driven storytelling, covering data collection, analysis, and visualization in the context of journalism and media.

An undergraduate course introducing Python programming for data analysis, with applications in social science and communication research.

A graduate course on computational text analysis methods for social science research, covering topic modeling, word embeddings, sentiment analysis, and large language models.

An undergraduate course on data-driven storytelling, covering data collection, analysis, and visualization in the context of journalism and media.

A graduate course on computational methods for media research, covering data collection, text mining, network analysis, and machine learning applications in communication studies.