3 credits
Fall 2026 Lecture Lower Division
This course introduces students to computational linguistics, a subfield of linguistics that studies natural languages from a computational perspective. The course covers both the theoretical and engineering topics ranging from aspects of formal linguistic structure to tools of language technology. The course will provide an understanding of the essential characteristics and differences between fields of inquiry such as computational linguistics, natural language processing (NLP), machine learning, and artificial intelligence (A.I.). There are no prerequisites and students are not expected to have any previous programming background, although the course introduces students to Python 3 programming language. Python is the ideal choice for NLP and AI due to its robust capabilities, strong community support, flexibility, and readability. It is a requirement for all NLP practitioners.
Learning Outcomes1Identify and describe key concepts of and common methods in computational linguistics.
2Explain the role of computational linguistics in the broader context of linguistics and artificial intelligence.
3Implement computational linguistics tasks with robust Pythonic code using state-of-the-art NLP libraries such as natural language processing toolkit (NLTK) and spaCy.
4Acquire the ability to write programming projects in Python.
5Analyze linguistic patterns in a natural language using Pythonic coding skills.
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