CS 5744

Language Modeling

Course Description

Course information provided by the 2025-2026 Catalog.

This course constitutes an introduction to computational natural language modeling. Language modeling is at the heart of many of today’s most exciting technological achievements, including AI assistants, automated translation, autonomous research, coding agents, and Internet search. The course will introduce core problems and methodologies in language modeling, including machine learning techniques, model design, task formulation, and evaluation. The course covers the core techniques of the field, through both instruction and hands-on implementation.

Enrollment Priority Enrollment limited to: Cornell Tech Students only. Recommended prerequisites: CS 4780 /5780 or CS 5785 or CS 5781 or equivalent machine learning course experience.

Last 4 Terms Offered (None)

Learning Outcomes

• Mastery of the key algorithms for training and executing core language modeling methods.
• Understanding of the limitations and computational costs of language modeling methods.| Practical ability to implement, debug, optimize, and tune language modeling models. Language data analysis and evaluation skills.
• Facility to compare and contrast different systems along facets such as accuracy, deployment, and robustness.

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