The University of Texas at Austin
MA in Computational Linguistics
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Admission Snapshot
Typical admitted student: A bachelor's degree in linguistics, computer science, or a related field with a minimum GPA of 3.0 is required, along with programming experience in Python and foundational knowledge in algorithms or statistics.
About This Program
An interdisciplinary graduate concentration that educates students in the theory, technologies, and applications of natural language processing and computational linguistics.
Career Outcomes
Lead as NLP Engineer in Cross-Industry AI with natural language processing expertise
- 1. NLP Research Scientist
- 2. Computational Linguist
- 3. Machine Learning Engineer (Language)
- 4. AI Language Model Developer
What You'll Learn
- Design and implement NLP models for text analysis and generation.
- Analyze linguistic structures using computational methods like parsing and semantic role labeling.
- Apply machine learning techniques to language data for tasks such as translation and sentiment analysis.
- Evaluate discourse coherence and multi-sentence language processing in AI systems.
Curriculum Highlights
First-year requirements in syntax and semantics are followed by advanced seminars in computational semantics, large language models, and applied text analysis.
Top Employers
Top employers include tech companies like Google, Meta, Amazon, and Microsoft, as well as research institutions and AI startups.
Admissions
A bachelor's degree in linguistics, computer science, or a related field with a minimum GPA of 3.0 is required, along with programming experience in Python and foundational knowledge in algorithms or statistics.
Application Materials
- Statement of Purpose: Required
- Letters of Recommendation: 2β3
- Resume: Required
- Transcripts: Official transcripts required
Academic Requirements
- Degree Required: Bachelor's degree
- GRE/GMAT: Optional
- TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)
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