Computational Linguistics, Analytics, Search and Informatics
Fleming Building, room 283
This is a unique interdisciplinary degree that provides a solid foundation in both computer science and linguistics graduate coursework as well as several courses focused on data-driven linguistics, computational linguistics and information processing. The training is aimed at preparing students for careers in areas such as predictive text messaging, search engines, question-answering, interactive virtual agents and machine translation.
Distance Education Option
Students can take individual courses toward a master's degree or graduate certificate through distance education (online). For more information, connect with the individual graduate program directly.
Due to the hands-on learning experience, some courses must be taken on campus. This is a hybrid program.
Students must complete at least 32 hours of approved graduate study, including a 2-credit capstone course focused on a publishable research project, which will run in conjunction with an internship or a CU-based research project. As part of the capstone, students will be evaluated by their employer or industry project manager. Students will also prepare a technical report on the completed project that the program directors and project leader will jointly evaluate. A minimum course grade is a B and a minimum GPA for graduation is a 3.0.
To fulfill core requirements defined below, students must take graduate breadth courses in 3 different breadth bins. This includes core computer science (bins 1 and 3) and core CLASIC (bin 2).
Required Courses and Credits
|Core Linguistics Courses||9|
|Choose two of the following:|
|Morphology and Syntax|
or LING 6450
|Semantics and Pragmatics|
Any LING course at the 5000-, 6000- or 7000-level (subject to advisor approval)
|Core Computer Science Courses||6|
|Bin 1 (choose one) 1|
|Design and Analysis of Algorithms|
or CSCI 5444
|Introduction to Theory of Computation|
or CSCI 5714
|Principles of Numerical Computation|
or CSCI 5646
|Numerical Linear Algebra|
|Bin 3 (choose one) 1|
|Datacenter Scale Computing - Methods, Systems and Techniques|
|Object-Oriented Analysis and Design|
|Fundamental Concepts of Programming Languages|
|LING/CSCI 5140||CLASIC Capstone||2|
|Core CLASIC Courses|
|CSCI/LING 5832||Natural Language Processing (Satisfies Bin 2 requirement)||3|
|CSCI 7000/LING 7800||Current Topics in Computer Science (Computational Lexical Semantics)||3|
|CSCI/LING 7565||Computational Phonology and Morphology||3|
|Choose two of the following:||6|
|Network Analysis and Modeling|
|Neural Networks and Deep Learning|
|Advanced Machine Learning|
|Current Topics in Computer Science (Inference, Models & Simulation for Complex Systems)|
|Topics in Nonsymbolic Artificial Intelligence (Probabilistic Models of Human & Machine Intelligence)|
|Topics in Nonsymbolic Artificial Intelligence (Representation Learning for Language)|
|Introduction to Computational Corpus Linguistics|
|Open Topics in Linguistics (Machine Learning and Linguistics)|
|Topics in Language Use (Formal Models of Linguistics)|
|Topics in Comparative Linguistics (Computational Grammars)|
|Topics in Logic|
Any other CSCI or LING course at the 5000-, 6000- or 7000-level
Any Core course listed above (not already taken)
|Total Credit Hours||32|
Visit the computer science department website for a full list of course options in each of the 3 breadth bins. (Updated every two years.)
The program is intended to:
- Provide a solid foundation in computer science, data-driven linguistics and natural language processing graduate coursework.
- Educate graduates to be specialists in the application of computers to the processing of natural languages, such as English, Chinese, Arabic and Urdu.
- Prepare students for jobs in the field of computational linguistics, also known as text analytics, natural language processing and informatics, a field critical to the success of mainstream global businesses who compete for employees qualified to address these needs.