Ntrl Lang Process/Text As Data

Catalog description

Natural Language Processing and Text as Data (3) In recent years, the quantity and quality of text data have dramatically increased, driving a surge in demand for tools to effectively analyze this data and unlocking new approaches to language modeling. This course introduces natural language processing (NLP) and text as data, with a strong focus on modern deep learning architectures. Using Python, the class covers fundamental NLP techniques, including text preprocessing, text classification, topic modeling, text embeddings, benchmarking and evaluation, transfer learning, attention mechanisms, transformers, and large language models (including generative LLMs). Through hands-on implementation of deep learning models, students understand how neural networks can capture complex linguistic patterns and relationships in text data. Applications involve working with data such as product reviews, tweets and other social media posts, news articles, and open-ended surveys to answer questions in domains like the social sciences and business. Crosslist: CSC-487. Recommendation: CSC-668.