INST425

Students will explore AI-driven approaches for analyzing large-scale text data, with applications spanning the social sciences, humanities, journalism, and related fields. Topics include foundational and advanced natural language processing (NLP) techniques such as word statistics, lexicons, clustering, topic modeling, text classification, and information extraction. The curriculum also examines the capabilities and limitations of large language models, including BERT and ChatGPT, for text analysis. Through hands-on Python-based projects and engagement with contemporary research in computational social science and cultural analytics, students will learn to extract meaningful insights from textual data. The experience culminates in an independent project that applies AI text analysis methods to a domain of the student's choice, supported by structured guidance and mentorship.