In their first year, graduate students interested in computational linguistics usually take the required courses related to syntax and semantics (some students opt to take Semantics I in their second year),
as well as Research in Computational Linguistics. Beginning in their second year, students interested in continuing in computational linguistics choose courses from the following: - Natural Language Processing (Ray Mooney, Computer Science)
- Applied Natural Language Processing (Jason Baldridge)
- Concepts of Information Retrieval (Matt Lease, ISchool)
- Courses offered by the Department of Statistics and Data Sciences
- Machine Learning (Computer Science)
Advanced courses and seminars in computational linguistics are offered as LIN 386/LIN 392. They are typically taught in the spring semester. Past topics have included: - Computational semantics
- Grounded models of meaning
- Applied text analysis
- Data-Intensive Computing for Text Analysis
- Semisupervised Learning for Computational Linguistics
- Natural language learning
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