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Interdisciplinary Studies with a concentration in Computational Linguistics Master's
Master of Science (M.S.)
Program type:
Major
Format:
Hybrid
Est. time to complete:
2 years
Credit Hours:
30
Harness the power of big data and machine learning to create systems to solve problems
and improve human-computer communication.
A concentration in Computational Linguistics brings together coursework in linguistics
and computer science to develop two different skill sets in students.
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Request More InfoWhy earn a degree in Interdisciplinary Studies with a concentration in Computational Linguistics Master's?
Computational linguistics (CL) is the scientific study of language from a computational perspective. CL lives at the intersection of language and technology; it is inherently interdisciplinary. The CL concentration in the interdisciplinary studies master’s program brings together course work in linguistics and computer science to develop two different skill sets in students.
First, our graduates develop keen skills in linguistics and linguistic analysis, learning how languages work in the abstract. This knowledge can then be applied to the design of computational systems for automating linguistic analysis.
The second major goal of the concentration is for students to develop a thorough knowledge of the methods used in automated natural language processing (NLP), as well as the programming skills to undertake research in computational linguistics.
These two skill sets will be augmented by a pair of courses selected to strengthen background relevant for the student’s intended career path. These course sequences are to be selected in consultation with the concentration advisors; possible topics include learning technologies, digital data curation, business analytics or information science.
For additional information, please visit https://interdisciplinarystudies.unt.edu/concentrations/computational-linguistics-ms.
Marketable Skills
- Work independently across two or more disciplines
- Teamwork
- Function across organizational silos through discipline integration
- Synthesize information and results
- Write in a professional and coherent manner
Interdisciplinary Studies with a concentration in Computational Linguistics Master's Highlights
Whether you are a young recent graduate of a bachelor’s program or have been in the
workforce for years, you can hone your talents for future employment where broad knowledge,
advanced research, and effective communication skills are in high demand.
The program allows you to take classes in person at our Frisco or Denton campuses,
or you can choose to complete it 100% online.
Our online master’s in Interdisciplinary Studies is ranked a Top 25 Program in the
Nation by MyDegreeGuide.com.
Through UNT’s Interdisciplinary Studies program you will learn to sift through information
and produce a body of work that synthesizes multiple perspectives, arriving at a more
comprehensive understanding of the important issues.
The interdisciplinary studies program offers students a high degree of flexibility
in designing a program of study that cuts across disciplinary boundaries.
Employers recognize the value of individuals who are open-minded, and who call upon a wide array of unconventional tools to solve intricate problems.
Career Outlook
Interdisciplinary Studies with a concentration in Computational Linguistics Master's Courses You Could Take
Morphology (3 hrs)
Core concepts of word structure and different theories of word formation are used
to analyze data from a variety of languages. Students consider the relation of morphology
to language change.
Computational Linguistics I (3 hrs)
Introduction to the computational analysis of language, focusing on core methods in
natural language processing. Combination of theory and implementation (in Python).
Fundamentals of Artificial Intelligence (3 hrs)
A broad understanding of the basic techniques for building intelligent computer systems
and how AI is applied to solve problems. The emergent nature of intelligent behavior
through robust and efficient sensation, knowledge representation, and decision making
are demonstrated through a series of hands-on demonstrations and tutorials. Ethical
implications of automation and autonomy of machines are discussed through case studies.
This exposure provides the breadth to understand the capabilities to begin a deeper
exploration of artificial intelligence.
Pattern Recognition (3 hrs)
Study of the fundamentals of pattern recognition techniques including Bayesian decision
and estimation, non-parametric methods, multi-class classifiers and feature selection
methods.
Natural Language Processing (3 hrs)
Introduction to natural language processing; modern theories of syntax; context-free
parsing; transformational syntax and parsing; augmented transition networks; and survey
of natural language processing systems.
Research Design in Linguistics (3 hrs)
Provides an introduction to research methods in linguistics and applied linguistics/ESL
with a focus on empirical research and the social and behavioral aspect of language
science. Covers a range of techniques for conducting linguistic research including
language data elicitation, data compilation, and data mining.
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