The Computing and Linguistics major provides multidisciplinary training in the computational study of human language, the development of systems for natural language processing, and the automated analysis of textual data in applications in the humanities, social sciences, and sciences.
Computing and Linguistics Major
Students learn the foundational tools and methods that underlie this work, including areas of computer science, statistics and data science, and linguistics, and apply them to some empirical domain, through coursework and an independent research project in the senior year.
Two Degree Tracks
The B.A. in Computing and Linguistics exposes students to the fundamental ideas and foundational techniques of the field, while the B.S. provides more extensive training and engagement in research, preparing students for graduate work in the area.
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B.A. Degree
11 term credits
1-semester senior essay requirement
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B.S. Degree
14 term credits
2-semester senior essay requirement
Course Requirements
- Statistics prerequisite: S&DS 100, 10X, 123, or 220, or comparable background in statistics
- Programming prerequisite: CPSC 100 or 112 or comparable programming experience
- Linguistics prerequisite: Any 100 level course in LING
One of:
- MATH 244 Discrete Math
- LING 224 Mathematics of Language
- CPSC 202 Mathematical Tools for Computer Science
One of:
- MATH 222 or 225 Linear Algebra
For B.A. degree: S&DS 238 Probability and Statistics
For B.S. degree:
Option 1:
- S&DS 240 or 241 Probability Theory
- S&DS 242 Statistics
Option 2:
- S&DS 238 Probability and Statistics
- one other S&DS course numbered 230 or ≥ 242
Choose 2 for B.A. and 3 for B.S.:
- LING 232 Phonology 1
- LING 253 Syntax 1
- LING 263 Semantics 1
- CPSC 201 Introduction to Computer Science
- CPSC 223 Data Structure
One of:
- LING 235 Phonology 2
- LING 254 Syntax 2
- LING 264 Semantics 2
One of:
- CPSC 477 Natural Language Processing
- LING 227 Language and Computation
One of:
- S&DS 265 Introductory Machine Learning
- S&DS 365 Intermediate Machine Learning
- CPSC 481 Introduction to Machine Learning
Additional course in computational linguistics and machine learning or in other disciplines that make use of computational analysis of language data. In addition to the course listed above under Advanced Courses, the following is an incomplete list of others that might apply:
Choose 1 for B.A. or 2 for B.S.:
- LING 225 Computing Meanings
- LING 238 Encoding Speech in Minds and Machines
- LING 380 Neural Networks Models of Linguistic Structure
- CPSC 677 Advanced Natural Language Processing
- CPSC 464 Topics in Foundations of Machine Learning
- CPSC 470 Artificial Intelligence
- CPSC 452 Deep Learning Theory and Applications
- CPSC 453 Unsupervised Learning for Big Data
- CPSC 468 Computational Complexity
- CPSC 365/366 Algorithms
- PSYC 437 Minds, Brains and Machines
- PHIL 267 Mathematical Logic
For B.A.: In one semester of the senior year, students will participate in a capstone seminar, which will involve both discussion of their research and presentations by researchers in the field from within Yale and outside. Student research may be independent (supervised by a Yale faculty member with relevant expertise) or part of a group project carried out by capstone seminar participants.
For B.S.: In both semesters of the senior year, students will participate in a capstone seminar, which will involve both discussion of their research and presentations by researchers in the field from within Yale and outside. Student research may be independent (supervised by a Yale faculty member with relevant expertise) or part of a group project carried out by capstone seminar participants.
