Major • STEM

Computational Linguistics

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About this major

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.

STEMTechnologyLinguisticsAIInterdisciplinary

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Curriculum snapshot

Introduction to Computational Linguistics

Covers the basic principles of how computers process and understand human languages.

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.

Career outcomes

  • Computational Linguist
  • Natural Language Processing Engineer
  • Data Scientist
  • AI Researcher
  • Speech Recognition Specialist
Intern$40k-$60k
New Grad$60k-$80k
Mid-Level$80k-$120k
Senior+$120k-$160k+

Pros

  • High demand in tech industry
  • Interdisciplinary skill set
  • Opportunities in AI and machine learning

Considerations

  • Requires strong programming skills
  • Constantly evolving technology
  • Interdisciplinary nature may require additional study

Similar majors

Computer Science

Focuses on the theoretical and practical aspects of computing; foundational for computational linguistics.

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Linguistics

Studies the structure and meaning of languages; provides necessary knowledge about language for computational applications.

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Artificial Intelligence

Involves creating intelligent machines; overlaps with NLP in creating language understanding systems.

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Data Science

Focuses on analyzing and interpreting complex data; computational linguistics often involves large language datasets.

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Cognitive Science

Explores the mind and intelligence, including language processing; relevant for understanding human language interaction with machines.

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