Natural Language Technology

University of Washington Professional and Continuing Education ETPL
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.

Financial information

Total tuition

$10,967.00

Total required fees

$0.00

Books and supplies

$0.00

Locations

Seattle, Online

Instructional methods

Online, E-learning, or Distance Learning

Is this program offered on evenings and weekends?

Yes

Program details

8 Months

Length of training

Certificate

Award type

N/A

Credits

N/A

Clock Hours

Additional details

Award name

Certificate

Education Prerequisites

No Selection

Prerequisite courses and other requirements

Is this program approved to train veterans?

No

Program languages

English

Certification/license obtained as part of training program

Certification/license test preparation provided

Employment performance results

Program type

Language Interpretation and Translation

Completion rate

65%

Employment rate

67%

Typical (median) hourly earnings

$85.10

Typical (median) annual earnings

$154,380.00

Top industries for graduates

Program type

Language Interpretation and Translation

Other Industries

67%

Information

33%

Student characteristics

Enrollment
Number of students completing the program
22
Completion rate
65%
Average number of students who completed each year
7
Gender
Male
61%
Female
39%
Race
American Indian or Alaska Native
0%
Asian
55%
Black or African American
0%
Hispanic
0%
Native Hawaiian or Other Pacific Islander
0%
White
45%
Multi-racial
0%
Other
0%
Age
Under 20
0%
20 to 29
50%
30 to 39
38%
40 to 49
12%
50 and over
0%
Prior education

Data is unavailable for one of several reasons: In some cases, the institution has not provided the Workforce Board with data to independently evaluate program performance. We encourage all schools to provide this data on an annual basis. In other cases, the program joined Career Bridge recently and student data has not been reported yet. In other cases, the program is too small or too new to provide reliable results.