Introduction to Computational Linguistics
Covers the basic principles of how computers process and understand human languages.
Difficulty
Moderately challenging
Students rate Computational Linguistics 3.5/5 for difficulty across 6 ratings.
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3.5/ 5
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What makes this major demanding?
Worth it?
100% would recommend it
Based on 6 reviews across 2 schools
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Curriculum and careers
Computational Linguistics is an interdisciplinary field combining computer science and linguistics to understand and develop technologies that process natural language. Students learn about language structure, machine learning, and how to build systems like speech recognition and language translation tools.
Core course themes
Natural Language Processing
Focuses on algorithms and models for processing natural language data, including syntax and semantic analysis.
Machine Learning for Language
Explores machine learning techniques and their application to linguistic data.
Syntax and Semantics
Examines the structure and meaning of language, providing foundational knowledge essential for computational analysis.
Speech Recognition and Synthesis
Teaches the technology behind converting speech to text and vice versa, including acoustic modeling.
Language Data and Corpora
Studies the collection and analysis of language data used in computational models.
Common roles
- Computational Linguist
- Natural Language Processing Engineer
- Data Scientist
- AI Researcher
- Speech Recognition Specialist
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Computational Linguistics by school
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Community
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Student reviews
MixedCourses & teaching
Great major, super niche (if you like that type of thing), and the cohorts are super small and tight-knit. Curriculum-wise, however, it’s quite new so it’s half comp sci classes half linguistics classes. And I think they just implemented a capstone project. I don’t think they do that good of a job of marrying both disciplines to converge it into an AI/LLM-focused major, so I’d say that you would have to seek opportunities for learning those aspects of Comp Ling outside of the classroom. Nonetheless, faculty is great and the linguistics aspect of the major gives you an edge and various options for what you want to do in the future. I don’t think any of my peers in the same major are doing the same thing so I think that’s pretty cool.
Apr 2026
PositiveCourses & teaching
5 required CS classes. If you are better at reading and writing CS does have: A learning curve 103/104. Linguistics has some more quantitative courses with pragmatics(semantic trees/logic) & morphology(more semantic trees/real world applications). Many research opportunities which are good to get your foot in the door for grad. Opportunities to work in AI: I have a minor in AI and there’s a lot of intercept.
Apr 2026
MixedAdvice & things to know
The linguistics community is really small and tight knit and pretty welcoming but you have to be super careful about what classes you take. Since compling is a dual program between the school of engineering and liberal arts, you might have to take extra credits beyond 128 to graduate because of credit requirements from Dornsife (liberal arts)
Mar 2026
PositiveCareers & next steps
Fantastic major for people who aspire to become a software engineer. Enough CS core requirement to get internships and be ready for the workforce.
Apr 2026
PositiveCareers & next steps
Good balance between linguistics and CS, with multiple career pathways in research and software engineering.
Mar 2026
PositiveAdvice & things to know
This major is unique to UCLA, which contributed to my decision to commit here.
Apr 2026
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