LING 582: Advanced Statistical Natural Language Processing


This course explores techniques and key concepts behind the rapidly evolving state-of-the-art in natural language processing (NLP).

Rather than attempting to cover all the many advances in NLP during the past decade, this class instead aims to examine important trends and key concepts such as representation learning, structured prediction (parsing), sequence tagging, attention mechanisms, and forms of transfer learning, while offering a flexible plan of study by allotting time to tailor the course to the interests and needs of students.

Functioning much like a seminar, students will work together or individually on a semester-long research research project, analyze approaches, and grow comfortable reading, discussing, and presenting topics and technical papers of interest. Approximately one meeting a week will be devoted to in-class programming exercises designed to reinforce concepts covered in the course and foster data science skills (data exploration, visualization, evaluation metrics, technologies for reproducibility, HPC, cloud computing for model training, etc).

The main programming language used in the course will be Python (3.7).


Please see the course syllabus for details.

Locations and Times

MWF 11:00AM - 11:50AM in ECE, Room 258


NameGus Hahn-Powell
OfficeDouglass 228
Office HoursMW 1PM - 3PM by appointment