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Natural Language Processing M.S.

Introduction

Natural Language Processing (NLP) focuses on the development of computer programs to understand, generate, and learn from human language. It is a fundamental capability of artificial intelligence, and provides algorithms, methods and tools for analyzing text or speech for applications including conversational agents, machine translation, question answering, knowledge discovery, and sentiment analysis. The University of California, Santa Cruz professional Master of Science in Natural Language Processing program provides an education that has both depth and breadth in the core algorithms and methods used for NLP, and integrates foundational skills in data science and linguistic theory to prepare graduates to work in the field of natural language processing in industry, governmental agencies or nonprofit organizations. The degree is offered through the UCSC campus in Silicon Valley, enabling connection and collaboration with local industry and a focus on career development. Students are expected to complete coursework in four to five academic quarters, without leaves of absence.

Course Requirements

The minimum credit requirement for the M.S. Degree in Natural Language Processing is 59 credits. All courses must be taken for a letter grade with the exception of seminar courses.

Core Courses

All students are required to take the following six core courses (30 credits):

NLP 201Natural Language Processing I

5

NLP 202Natural Language Processing II

5

NLP 203Natural Language Processing III

5

NLP 220Data Science and Machine Learning Fundamentals

5

NLP 243Deep Learning for Natural Language Processing

5

NLP 244Advanced Machine Learning for Natural Language Processing

5

Electives

In addition, students are required to take two elective courses from the list below (10 credits):

NLP 245Conversational Agents

5

NLP 255Topics in Applied Natural Language Processing

5

NLP 267Machine Translation

5

NLP 270Linguistic Models of Syntax and Semantics for Computer Scientists

5

CSE 245
/LING 245/CMPM 245
Computational Models of Discourse and Dialogue

5

CSE 272Information Retrieval

5

CSE 290CAdvanced Topics in Machine Learning

5

CSE 290KAdvanced Topics in Natural Language Processing

5

Seminar

Students are encouraged to take the NLP seminar each time it is offered, however a maximum of 4 credits of NLP 280 can be counted toward the 59 credits required for the degree.

All students are required to take the following seminar course at least twice (4 credits):

NLP 280Seminar in Natural Language Processing

2

Capstone Courses

NLP M.S. students are required to take all courses in the following capstone series (15 credits):

NLP 271ACapstone I: Recent Research in NLP

5

NLP 271BCapstone II: Natural Language Processing

10

Transfer Credit

The NLP M.S. program does not accept transfer credit or course substitutions from other institutions. Course substitutions for elective courses taken at UCSC will be considered by petition.

Capstone Requirements

The capstone requirement for the M.S. Degree is fulfilled through an application team project. Students are expected to work on their capstone requirement over the spring and second fall quarters. Teams will consist of three to five students, who will work collaboratively on the project.

The teamwork will be spread over a 5-credit class in the spring quarter (NLP 271A) and a 10-credit class in the second fall quarter (NLP 271B) to constitute the complete 15-credit capstone experience.

In NLP 271A, student teams will explore the NLP research literature and present a proposal for their capstone project. In NLP 271B, student teams will complete their capstone project and present the final results to the public.

In NLP 271A, student teams will review papers from the research literature and get matched to mentors from either industry or the UC Santa Cruz NLP program faculty, based on their interests. Mentors will meet with their teams at least once a week to evaluate progress and provide guidance. At the end of the quarter, each team will produce a 10-page written project proposal, and orally present it to the NLP Industry Advisory Board. The proposal will cover the topic for their capstone project, the background, the data sources, the high level design, and a milestone schedule. The proposal will need to be approved by the capstone coordinator (typically, the executive director of the program).

In NLP 271B, teams will complete the implementation of their capstone project, under guidance from their mentors. At the end of the quarter, each team will submit a 10-page written report and present their work at the annual UC Santa Cruz NLP Capstone Workshop. Student evaluations will be based on the quality of the team project, individual class participation, and peer evaluations (in which students evaluate the contributions of their teammates).

All students will be required to either present a poster or oral presentation at the UCSC NLP Capstone Workshop, which will be an integral part of the capstone evaluation. The Capstone Workshop will be an annual event taking place at the end of each fall quarter to which program faculty, students, and members of the Industry Advisory Board will be encouraged to attend. The workshop will also serve as a general outreach to NLP scientists in local industry and government.

Planners

Students can complete the M.S. Degree requirements in either four quarters or five quarters depending on the pace at which they wish to complete the degree and if they would like to engage in optional independent research during the program. By the end of the second week in their first fall quarter in the program, students are required to inform their graduate student advisor if they plan to complete the M.S. Degree requirements in four quarters or five quarters.

The sample planners below may include summer internships or independent studies to engage in research. These are not required and do not bear academic credit.

Sample Planner for Completing the Program in Four Quarters (Fall, Winter, Spring, Fall)

Fall Quarter 1 (15 credits) NLP 201 (5 credits)
NLP 220 (5 credits)
NLP 243 (5 credits)
Winter Quarter 2 (12-17 credits) NLP 202 (5 credits)
NLP 244 (5 credits)
Elective 1 (5 credits) - alternatively can be completed in Spring Quarter
NLP 280 (2 credits)
Spring Quarter 3 (17 credits) NLP 203 (5 credits)
NLP 271A (5 credits)
Elective 1 / Elective 2 (5 credits) - depends on whether an elective was completed previously in first Winter Quarter
NLP 280 (2 credits)
Summer Session Internship or Independent Study (optional)
Fall Quarter 4 (10-15 credits) NLP 271B (10 credits)
Elective 2 (5 credits) - not required if 10 credits of elective coursework were completed previously

Sample Planner for Completing the Program in Five Quarters (Fall, Winter, Spring, Fall, Winter)

Fall Quarter 1 (15 credits) NLP 201 (5 credits)
NLP 220 (5 credits)
NLP 243 (5 credits)
Winter Quarter 2 (10-12 credits) NLP 202 (5 credits)
NLP 244 (5 credits)
NLP 280 (2 credits) - alternatively can be completed in second Winter Quarter
Spring Quarter 3 (12-17 credits) NLP 203 (5 credits)
NLP 271A (5 credits)
Elective 1 (5 credits) - alternatively can be completed in second Fall or Winter Quarters
NLP 280 (2 credits)
Summer Session Internship or Independent Study (optional)
Fall Quarter 4 (10-15 credits) NLP 271B (10 credits)
Elective 1 (5 credits) - depends on whether an elective was completed previously
Elective 2 (5 credits) - alternatively can be completed in second Winter Quarter
Winter Quarter 5 (10-12 credits) Elective 1 (5 credits) - required if not completed previously
Elective 2 (5 credits) - required if not completed previously
NLP 280 (2 credits) - required if second offering of the seminar was not completed previously

Review of Progress

Normative time for completion of the NLP M.S. program is four quarters (fall, winter, spring, and an additional fall term). Alternatively, students can complete the program in five quarters (fall, winter, spring terms, and an additional fall and winter) if they wish to pursue a less intensive schedule or participate in optional internship and research opportunities during the program. Engagement in an internship or independent research is not required by the NLP M.S. program. Students are expected to maintain full-time enrollment for the duration of the program and complete all degree requirements within four to five quarters. Students are required to inform their Graduate Student Advisor by the end of the second week of their first fall quarter if they plan to complete the M.S. Degree requirements in four quarters or five quarters.

All courses, with the exception of the NLP 280 seminar, are offered once per academic year. If a student fails a core course, they will be required to retake and pass that course the following year when it is offered. If a student fails an elective course, they may make up those credits by passing an additional elective course in a subsequent quarter. Students receiving two or more unsatisfactory grades (U or letter grade below B-) are not making adequate progress and will be recommended for academic notice for up to three quarters of registered enrollment. Should a student fail a course while on academic notice, the department may request the graduate dean to dismiss the student from the graduate program. If after being removed from probation, the student again fails a Baskin School of Engineering course, they will return immediately to academic notice. Taking a leave of absence does not count as enrollment.

Students not making adequate progress toward completion of degree requirements (see the Graduate Student Handbook for policy on satisfactory academic progress) may be recommended for academic notice. Students who violate the terms of their academic notice are subject to dismissal from the program.

Applying for Graduation

All candidates for a degree must submit an Application for the Master's Degree to the Graduate Advising Office by the date stated in the Academic and Administrative Calendar for the quarter you wish to receive the degree. Failure to declare candidacy by the deadline means that you cannot be considered a candidate until the next term. For more information about applying for graduation, visit the Baskin School of Engineering Graduate Studies website.