This course introduces the theory and practice of cultural data mining, focusing on the use of Artificial Intelligence (AI) to discover meaningful patterns and generate new insights from large-scale cultural datasets. It provides students with the foundational methods for collecting, preparing, and analyzing cultural data.

The course aims to equip students with the analytical and interpretive skills to mine vast archives of texts, images, and structured data for hidden connections and trends. We will explore the full pipeline of a data project, from acquiring raw data via web scraping and OCR to applying AI-driven techniques like text mining, topic modeling, and computer vision. Crucially, the course emphasizes that data mining in the humanities is an interpretive act.

Students will learn to critically evaluate the patterns revealed by algorithms, understand their limitations, and synthesize computational findings with context-rich humanistic inquiry. By the end of the course, students will be able to design and execute a small-scale data mining project, from data acquisition to final presentation.