DTSC 5731 - Text Data Processing and Analysis

3 hours

Provides a comprehensive introduction to computational techniques for processing, analyzing, and interpreting text data, with a focus on natural language processing (NLP) and its applications in big data and data analytics. Students explore key topics, including web scraping, text data annotation, wrangling, and feature extraction. Also covers advanced methods such as word embeddings, transformers, knowledge graphs, and large language models. Practical applications include text classification, sentiment analysis, opinion mining, text generation, summarization, and prompt engineering. Concludes with discussions on model evaluation and generative AI. Through hands-on projects and case studies, students develop skills to tackle real-world text analysis challenges using state-of-the-art tools and techniques.