Bridge the Gap Between People and Machines
Next start date
When you talk to your mobile device or car navigation system — or it talks to you — you’re experiencing the fruits of developments in natural language processing. This field, which focuses on the creation of software that can analyze and understand human languages, has grown rapidly in recent years and now has many technological applications.
In this three-course certificate program, we’ll explore the foundations of computational linguistics, the academic discipline that underlies NLP. You’ll delve into the various technical principles of language processing techniques, gain expertise in specialized NLP algorithms, and consider the wide variety of applications for these cutting-edge skills.
Technically oriented professionals with some programming and statistics background who work with language and technology, or who want to enter the field.
If you're not a native English speaker, you’ll need to have at least basic English language skills to enroll. To learn more, see English Language Proficiency Requirements.
Because this offering is 100 percent online, no visa is required and international students are welcome to apply. For more information, see Admission Requirements for International Students.
Students must have a computer with high-speed Internet access, a Web browser and ssh client (available from Mac OS X, Linux, Cygwin, UWICK tools).
You earn the certificate by successfully completing all required courses. For more information, see Completing Your Program.
By completing this certificate program, you can earn up to 12 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 the first course of the certificate program.
You may be able to take individual courses
without enrolling in the certificate program;
check the course pages for details.
Basics for Computational Linguistics
Shallow Processing Techniques for Natural Language Processing
Deep Processing Techniques for Natural Language Processing
Advanced Statistical Methods in Natural Language Processing
Certificate in Natural Language Technology
Approved by the UW Department of Linguistics.
View this program's advisory board.
Each of our programs uses an advisory board to review content, guide design and recommend updates to ensure the program remains current as the field of study evolves. By tapping the minds of the top thinkers, doers and leaders in the field, we offer a transformational learning experience. The following individuals serve as the advisory board for this program.
Srinivas Bangalore, Lead Inventive Scientist, Interactions Corporation
Emily Bender, Professor, Department of Linguistics, University of Washington
Rovy Branon, Vice Provost, University of Washington Continuum College
David Bullock, Lexicographer and Writer, Beginner's ESL Text and Dictionary
Sabrina Burleigh, Research Manager, Language Modeling, Nuance Communications
Lesley Carmichael, Principal Program Manager Lead, Microsoft
Ciprian Chelba, Research Scientist, Google
Francine Chen, Senior Staff Research Scientist, FX Palo Alto Laboratory
Mike Cohen, Founder, stealth startup
Michael Gamon, Computational Linguist, Microsoft Research, Microsoft
Philip Harrison, Research Scientist, Allen Institute for Artificial Intelligence
Jim Hoard, Affiliate Assistant Professor, Department of Linguistics, University of Washington
Mark Johnson, Professor, Language Science (CORE), Macquarie University (Australia)
Ron Kaplan, Senior Director and Distinguished Scientist, Nuance Communications
Remy Sanouillet, Senior Computational Linguist, NetBase Solutions Inc.
Amarnag Subramanya, Research Scientist, Google
Joseph T. Tennis, Associate Professor, Information School, University of Washington
Michael Tjalve, Senior Program Manager, Speech, Microsoft; Affiliate Assistant Professor, Department of Linguistics, University of Washington
Clare Voss, Senior Computer Scientist, Army Research Laboratory
Richard Wojcik, Associate Technical Fellow (retired), Boeing
Richard Wright, Professor and Department Chair, Linguistics, University of Washington
With the exception of the one-time application fee, certificate program fees are charged on a quarterly basis. Payment is due when you register.
Course fees do not include any costs for class materials such as textbooks and software. The technology fee is based on the number of credits you are taking.
Drops, Withdrawals & Refunds
Enjoy the flexibility of online learning, which allows you to participate in class activities, assignments and discussions on your schedule, from anywhere. Experience cutting-edge technology and a supportive, diverse learning community.
Our special blended programs combine the convenience of online study with the vibrancy of in-person classes for a unique learning experience.
Not available for this program
Attend class in person at one of our convenient locations. You’ll engage face to face with your classmates and instructors as part of a highly interactive curriculum. An online learning management system may be required to access some course materials and assignments.
Associate Professor, Department of Linguistics
If you’re thinking about heading back to school, you’re probably also wondering how you’ll pay for it. To help you figure that out, we’ve put together a list of ways to help fund your education.
Learn how to apply cutting-edge tools and techniques to extract meaning from data sets ranging in size from gigabytes to petabytes.
Build a solid understanding of Java fundamentals, basic syntax and object-oriented programming concepts, and become skilled at writing Java code and developing applications.
Gain a solid understanding of localization processes and principles, and explore topics such as machine translation, terminology management and global content management systems.
Study the probability concepts and statistical methods at the core of machine learning algorithms and explore ways to apply these techniques to address business needs and real-world challenges.
Learn best practices for programming in the versatile Python language and acquire the skills to develop web applications and do back-end development.
Be at the forefront of scientific innovation by learning to transfer human competencies, such as language and communication, to computers.