Natural Language Processing
With the proliferation of language technologies in use, from smartphones in our pockets to analytic and predictive algorithms in use by individual, institution, private sector, and state actors, it is critical that students in computer science be familiar with the purposes for which linguistic data is used, and the algorithm and techniques used to process linguistic data computationally. This course blends computer science and linguistics to teach students the foundational and cutting-edge techniques in NLP, their various use cases, achievements and pitfalls, and the relationship between language processing techniques and methods within other subdisciplines within machine learning, artificial intelligence, and data science.
In this course, students will learn to:
- identify ethical and societal issues present in NLP use cases.
- define NLP use cases and commonly-used methods;
- identify useful NLP techniques based on data and task;
- describe the relationship between raw data, annotated data, and NLP tasks;
- design, implement, and evaluate experiments in NLP use cases;
- critically read and discuss NLP literature;
- connect achievements and failures in NLP to issues in data and algorithmic implementation;
2025 Fall Semester Details
Instructor(s)
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Instructor 4_b4a01f-dc> |
Nikhil Krishnaswamy 4_1ab8d2-bb> |
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Office 4_0fe0f0-db> |
CSB 362 4_418880-51> |
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Office Hours 4_3ff462-5a> |
T 15:30-16:30, Th 15:30-16:30 4_b37505-e5> |
Class Schedule
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Section 4_fb9170-a7> |
Schedule 4_7b09a2-a3> |
Location 4_d89863-cf> |
Instructor 4_c4f2e9-0d> |
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001 4_c1bdbe-df> |
MW 13:00 – 14:15 4_3dbf82-79> |
CSB 130 4_130cee-fd> |
Krishnaswamy 4_983ccf-64> |
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801 4_94fc11-da> |
MW 13:00 – 14:15 4_ca401b-2a> |
Zoom (link in Canvas) 4_3b1e40-2f> |
Krishnaswamy 4_521d86-ef> |
TA Information
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Name 4_254192-f9> |
Role 4_29769e-1b> |
Office Hours 4_f9379e-35> |
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Carine Graff 4_387040-d8> |
TA 4_d42f09-82> |
M 09:00-10:00, 15:00-16:00 (CSB 120, or contact on Teams for Online) 4_8bf456-42> |