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Master of Science in Computational Linguistics

Certificate in Natural Language Technology 

On This Page: Format | Courses | Cost | Earn Credit Toward Master's | Enroll in a Single Course | Admissions

Work at the forefront of natural language processing — a fast-changing field that’s behind innovations such as predictive text, voice assistants, information extraction and more.  

In this three-course certificate program, you’ll learn about the science that underlies natural language processing (NLP). You’ll delve into the various technical principles of language processing techniques and gain expertise in specialized algorithms. Along the way, you’ll get extensive hands-on experience with various NLP scenarios.  

Format

This eight-month certificate program is offered in a flexible format. You can attend class online, in person or both, based on your preference from week to week. In-person sessions are held on the UW campus in Seattle. 

The first course, held in the summer, meets in the late afternoon/evening. Other courses meet during the day. 

Courses

Students take 11 credits over two or three quarters. You must complete two required courses (LING 473 and LING 570) and one elective (LING 571 or 572). 

Summer Quarter  

LING 473: Basics for Computational Linguistics

Credits: 3

Computational linguistics builds on the theory and practice of multiple fields (linguistics, computer science and statistics) to design computer applications that involve the automatic processing of natural language speech or text by machines. This course is intended to reinforce the most important skills from contributing disciplines to prepare such students for further study in computational linguistics. We'll cover the following topics: UNIX and server cluster usage; probability and statistics (random variables and random vectors; conditional, joint and marginal probabilities; the chain rule; Bayes' rule; independence and conditional dependence); formal grammars and languages (Chomsky hierarchy, regular expressions and regular languages, context-free grammar and other grammar formalisms); finite-state automata and transducers; and algorithms and data structures.

This course is required only for the Certificate in Natural Language Technology. It is not required for the Master of Science in Computational Linguistics.  

Autumn Quarter

LING 570: Shallow Processing Techniques for Natural Language Processing

Credits: 4

This course covers techniques and algorithms for associating relatively surface-level structures and information with natural language corpora. Topics covered include tokenization/word segmentation, part-of-speech tagging, morphological analysis, named-entity recognition, chunk parsing and word-sense disambiguation. Students will also be introduced to linguistic resources that can be leveraged for these tasks, such as the Penn Treebank and WordNet.

Prerequisites:

LING 571: Deep Processing Techniques for Natural Language Processing

Credits: 4

This course covers algorithms for associating deep or elaborated linguistic structures with naturally occurring linguistic data, looking at syntax, semantics and discourse. It also explores algorithms that produce natural language strings from input semantic representations.

Prerequisites:

Winter Quarter

LING 571: Deep Processing Techniques for Natural Language Processing

Credits: 4

This course covers algorithms for associating deep or elaborated linguistic structures with naturally occurring linguistic data, looking at syntax, semantics and discourse. It also explores algorithms that produce natural language strings from input semantic representations.

Prerequisites:

LING 572: Advanced Statistical Methods in Natural Language Processing

Credits: 4

This course covers several important machine learning algorithms for natural language processing, including decision tree, kNN, Naive Bayes, transformation-based learning, support vector machine, maximum entropy and conditional random field. Students implement many of the algorithms and apply these algorithms to selected NLP tasks.

Prerequisites: LING 570 

Cost

The Certificate in Natural Language Technology costs an estimated $10,967 (2024–25). Each quarter, students also pay registration ($55) and technology fees ($4–$22). Costs for textbooks and other course materials are extra.

Earn Credit Toward Your Master’s Degree

By completing this program, you can earn up to eight graduate credits toward degree requirements should you later be accepted into the Master of Science in Computational Linguistics. To use these credits, you must obtain graduate nonmatriculated status before you register for autumn quarter.

Enroll in a Single Course

If you’re not ready to commit to the full certificate program, you can take a single course to see if the curriculum is a good fit for you. Learn more about single course enrollment. 

Admissions

Application Deadline

Applications for the July 2025 program start will open February 15, 2025. The application deadline is June 1, 2025.

Admission Requirements

  • Bachelor's degree
  • At least two years of programming experience, including knowledge of Python 
  • Knowledge of probability and statistics (equivalent to STAT 394 at the UW) 
  • Knowledge of data structures and algorithms (equivalent to CSE 373 at the UW) 
  • Demonstrated English language proficiency for applicants whose native language is not English

Application Steps

Step 1: Gather the following materials

  • A brief letter (250-word maximum) that describes your relevant experience, transferable skills, knowledge of the field and commitment to professional growth 
  • A resume that highlights how your education and any applicable experience fulfill the program's admission requirements 
  • One set of transcripts from all relevant institutions (unofficial transcripts are acceptable)

Step 2: Apply

Complete your application and submit your letter and resume online. Email your transcripts to pceapps@uw.edu.

Next, pay the $50 nonrefundable application fee. One to two business days after you submit your application, you’ll receive an email with a link to pay your fee.

After Applying

We review all applications together after the deadline. We'll contact you shortly after the deadline to let you know if you’ve been accepted to the program.

If you’re accepted, we’ll send you details about your first-term course, including information on how to register and pay your course fees. To ensure your spot in class, we recommend that you register by the priority registration deadline, which is four weeks before class begins. After that time, we may release your seat to another student. The final registration deadline is two days before the first class meeting.