Natural Language Processing

Catalog description

This graduate elective introduces deep learning methods for natural language processing, covering neural architectures such as CNNs, RNNs, transformers, and large language models. Students gain hands-on experience implementing and evaluating NLP models in PyTorch, with emphasis on representation learning, attention, transfer learning, prompting, and real-world applications.