Natural Language Processing
Explore modern natural language processing using machine learning and deep learning approaches. Examine linguistics fundamentals (syntax, semantics, distributional properties of language), machine learning models (classifiers, sequence taggers, deep neural networks), key algorithms for inference, and a range of applications. Build systems to do tasks including sentiment classification, text generation, and more. Computer Science 371N and 378 (Topic: Natural Language Processing) may not both be counted. Three lecture hours a week for one semester.
Prerequisites & course information
Explore modern natural language processing using machine learning and deep learning approaches. Examine linguistics fundamentals (syntax, semantics, distributional properties of language), machine learning models (classifiers, sequence taggers, deep neural networks), key algorithms for inference, and a range of applications. Build systems to do tasks including sentiment classification, text generation, and more. Computer Science 371N and 378 (Topic: Natural Language Processing) may not both be counted. Three lecture hours a week for one semester.
Sources
- Course catalogue ↗2026-2027