AI and Natural Language Processing
This course explores cutting-edge developments in artificial intelligence, machine learning, and computational linguistics, with a focus on deep learning techniques. Students work with unstructured and semi-structured text, transforming text into numerical vectors and converting higher-dimensional vectors into lower-dimensional ones for analysis and modeling. The course covers parts-of-speech parsing, information extraction, semantic processing, text classification, sentiment analysis, text embeddings, topic modeling, text summarization and generation, and question answering. Students explore large language models, particularly generative pretrained transformers (GPTs). This is a project-based course with extensive programming assignments.
Prerequisites & course information
Prerequisite: (1) MSDS 420-DL Database Systems or CIS 417-DL Database Systems Design and Implementation and (2) MSDS 422-DL Practical Machine Learning or CIS 435-DL Practical Data Science Using Machine Learning.
Sources
- Course catalogue ↗2026–2027