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COE4212804  - Introduction to Natural Language Processing - Spring 2023

Course Info:

The objective of this course is to introduce and teach the fundementals of problems, theories, algorithms and applications of Natural Language Processing (NLP).

Prerequisite Courses

Data Structures

Required Text(s)

 

Speech and Language Processing (3rd ed. draft) Dan Jurafsky and James H. Martin (html). 

Text1

  

Recomended Text(s)

- Jacob Eisenstein, Natural Language Processing (2018) [Available on bCourses] [G] Yoav Goldberg, Neural Network Methods for Natural Language Processing (2017)
- James Pustejovsky and Amber Stubbs, Natural Language Annotation for Machine Learning (2012)


Meeting Times:

- Thusday 13:30 - 16:30,  Location: C-211

Labs:

- Lab : No labs

Tentative Grading:

Evaluation Tool (*) Weight in %
Assignments,
Presentations and
Projects		 30
In-term Exams
- 1 Midterm		 30
Final 40
(*) After each type of assesment, some of the students may be called for an oral examination. The student's performance in the oral exam will affect the student's grades. If a student does not come for an oral exam or follow the specified exam rules, (s)he will get automatically score 0 (zero) points for that part of the assesment.


Tentative  Course Outline:

WEEK TOPIC(S)
1 Introduction
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Course Syllabus in PDF ()