Computer Science Master's Degree - Natural Language Processing
Natural Language Processing
Online Program Overview
Minimum GPA
Qualifying Exam
The Natural Language Processing (NLP) track is intended for students who wish to gain expertise in NLP technologies and applications. NLP technologies are of central importance in automating the analysis of text and speech databases and in enabling man-machine interactions through natural language. This track will help you develop leading edge knowledge of these technologies.
Before signing on to become an online graduate student with Columbia, I checked nearly every online degree program in the country. In evaluating all of the schools for quality of education, variety of course offerings, quality of faculty, reputation of school, I can affirm that Columbia has one of the best programs in the country and by far the largest variety of course offerings! Returning to graduate school after 10 years in the work force was a major life decision for me. The CVN staff has been incredibly helpful and very understanding of the challenges faced by remote students, especially those returning to school after a long absence.
Admissions Requirements
Degree required for admission: Most candidates have completed an undergraduate degree in computer science. Applicants with degrees in other disciplines and a record of excellence are encouraged to apply; these applicants are required to have completed at least six prerequisites: 4 computer science courses covering the foundations of the field and 2 math courses.
Examples of computer science courses would be courses offered through an undergraduate computer science program: Intro to Computer Science (COMS W1004 or COMS W1007), Advanced Programming (COMS W3157), Data Structures and Algorithms (COMS W3134 or W3137), which is a prerequisite for most of our graduate-level courses, or/and Discrete Math (COMS W3203). For the math prereqs, students are encouraged to take linear algebra and differential equations.
Please note that these must be taken at a university (can be online) and must be grade- and credit-bearing. MOOCs such as courses on Coursera and edX do NOT meet this requirement. These courses are not offered here at Columbia Video Network, but may be taken at another online institution or your local university. Work experience does not waive this requirement.
GPA required: Most students admitted have earned a grade point average above 3.5 (out of 4.0); a GPA of at least 3.3 is required.
GRE requirements: General test required. A subject GRE test is not required but may be helpful in strengthening your application.
Competence in English: If you have not earned a degree from an undergraduate or graduate institution in which the instructional language was English, you may be required to take the TOEFL/IELTS.
Other application requirements: 3 recommendation letters, transcripts, resume, and a personal-professional statement are required. All application requirements in the Graduate Application must be completed as specified in the application.
We accept applications on a rolling basis, which means there are no deadlines to apply. Please submit your degree applications no later than 4 - 6 weeks before the semester you wish to enroll.
For answers to your most common admissions questions, please review our FAQ page here.
Overall Requirements
Students must complete at least 30 points of graduate coursework as outlined below.
1. Natural Language Processing Learning track requires:
- Breadth courses
- Required Track courses (9pts)
- Track Electives (6pts)
- General Electives (3pts)
2. 3 courses (9 points) are required for the track: COMS W4705 (NLP), COMS W4706 (Spoken Language Processing), and COMS E6998 (Advanced NLP Topics).
3. 2 track elective courses (6 points); at least one of these courses must be a 6000-level CS course.
4. 1 general elective graduate CS course (3 points) at 4000-level or above.
Description
Students must complete all core courses and selected electives for a total of 30 graduate points of academic work via CVN while maintaining a minimum grade point average of 2.7. All degree requirements must be completed within 5 years of the beginning of the first course credited toward the degree. This includes courses taken in the non-degree program.
Course List
For the most up to date course information, visit the CS NLP page.
Breadth Requirement
All students must complete the Breadth Requirement. Visit the breadth requirement page for a list of courses.
Required Track Courses
Students are required to complete the following 3 courses. Students who have taken equivalent courses in the past and received grades of at least a B may apply for waivers and take other CS courses instead.
- COMS W4705: Natural Language Processing
- COMS W4706: Spoken Language Processing
- COMS E6998: One additional topics course that focuses on NLP
Elective Track Courses
Students are required to complete 2 courses out of the following list; at least 1 course must be a 6000-level CS course. Since other departments vary their offerings considerably from year to year, it is possible to count such courses toward the MS degree; please propose courses you think might be suitable to the track advisor.
- COMS W4170: User Interface Design
- COMS W4172: 3D User Interfaces
- COMS W4252: Intro to Computational Learning Theory
- COMS W4701: Artificial Intelligence
- COMS W4771: Machine Learning*
- COMS W4721: Machine Learning for Data Science*
- COMS W4772: Advanced Machine Learning
- COMS W4995: Visit the topics courses page to see which apply for this track
- COMS E6901: Projects in Computer Science (advisor approval required)
- COMS E6998: Visit the topics courses page to see which apply for this track
- IEOR E4150: Probability and Statistics (formerly SIEO W4150)
- ECBM E6040: Neural Networks and Deep Learning
- EECS E6894: Deep Learning for Computer Vision and Natural Language Processing
- ELEN E4810: Digital Signal Processing
- ELEN E6829: Speech/Audio Processing-Recognition
* Due to significant overlap, students can receive credits for only one of these courses (either COMS W4771 Machine Learning or COMS W4721 Machine Learning for Data Science).
General Electives
Students are required to complete at least one Columbia graduate course, approved by the Track Advisor. Please complete a non-track approval form, get your advisor’s approval, and forward it to CS Student Services. At most 3 points overall of the 30 graduate points required for the MS degree may be non-CS/non-track.
Due to a significant overlap in course material, MS students not in the Machine Learning track can only take 1 of the following courses – COMS 4771, COMS 4721, ELEN 4903, IEOR 4525, STAT 4240, STAT 4400/4241/5241 – as part of their degree requirements.
Known non-track CS course: CSOR E4995 Topics in Computer Science and IEOR – Financial Software Systems
Known non-technical CS course: CSOR E4995 Topics in Computer Science and IEOR - Financial Software Systems
Tuition & Fees
2022 - 2023 Tuition & Fees
Please note that all tuition and fees are in U.S. dollars and are estimated. Tuition and most fees are prescribed by statute, and are subject to change at the discretion of the Trustees.
CVN Credit Tuition: $2,362 per point (Credit Hour)
CVN Fee: $395 non-refundable fee per course
Transcript Fee: $105 non-refundable one-time fee
Tuition Deposit: $1000 (More information on our Resources page)
Estimated cost of one nondegree course: $7,586
Estimated total cost of certification (four courses): $30,029.00
Estimated total cost of MS (ten courses): $74,915.00
*Estimated total cost of DES (ten courses plus a minimum of 12 research credits): $104,049.00
Graduate Admission Application Fee: $150 non-refundable one-time fee
Certification Program Application Fee: $150 non-refundable one-time fee
Late Registration Fee: $100 non-refundable fee
CVN Withdrawal Fee: $75, plus prorated tuition and all non-refundable fees
For example: A three-credit course would be $7,086 + transcript fee $105 (one-time) + CVN fee $395 = $7,586
*Assumes DES student enrolls in two six-credit research courses.
For Drop/Withdrawal fees and dates, refer to the Academic Calendar for the current term.
Please note: CVN no longer offers courses for audit.
Payment should be mailed to:
Columbia University
Student Account Payments
P.O. Box 1385
New York, NY 10008-1385
Before you mail your check or money order, please take careful note of the following requirements to ensure the timely processing of your payment: https://sfs.columbia.edu/content/pay-mail.
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