NATURAL LANGUAGE PROCESSING AND LARGE LANGUAGE MODELS 3 unit

Catalog description

Fundamental concepts and practical applications of Natural Language Processing (NLP) and Large Language Models (LLMs). Students will learn to process and analyze text data using tools such as Python, NLTK, spaCy, and Scikit-learn. Topics include text preprocessing, part-of-speech tagging, sentiment analysis, text classification, word embeddings, transformer architectures, prompt-based inference, and ethical challenges unique to LLMs. Emphasis on hands-on projects using real-world data to build job-ready skills in applied language technologies. Total of 54 hours lecture and 54 hours laboratory.