Natural Language Processing: Theory and Practice. 3 credits

Catalog description

This introductory to intermediate-level course in Natural Language Processing (NLP) provides a comprehensive exploration of both theoretical foundations and practical applications of NLP. It covers essential core principles, including regular expression, n-gram language models, text classification, part of speech tagging, word sense disambiguation, named entity extraction, vector semantics, context-free grammar, information retrieval, and question answering. The course further explores advanced topics, such as neural networks, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and conversational agents. Students will engage in programming assignments focused on key NLP applications, including chatbots, text generation, summarization, information extraction, question answering, sentiment classification, and building neural networks. The course culminates in term projects that address real-world NLP challenges, utilizing both foundational and cutting-edge techniques. Offered by Info Sciences & Technology . May not be repeated for credit.