CSCI 4152

Natural Lang Processing

Lec 01 and Lab B01 selected

This course presents strategies and techniques for natural language understanding by machines. The course will cover a selection of topics taken from the following three areas: parsing techniques used to represent sentence structure and discover ambiguities, the representation of word meanings and how sentence meaning can be derived from word meanings, and the application of context and world knowledge to the interpretation of language.

Sections

Lecture
Lab

From the syllabus

From the Fall 2026 syllabus by Vlado Keselj. Open the PDF

Grading

32%AssignmentsTentatively 3–5, including A0
32%Final exam3-hour, in person
10%Class presentation and participationIncludes attendance
26%Project deliverablesP0, P1, and report

Textbook

  • Speech and Language Processing, Daniel Jurafsky and James Martin

Course rules

Late work
Late assignments are not accepted; resolve deadline difficulties with the instructor before the deadline.
Assignment absence
Student Declaration of Absence forms may be used for assignment deadlines up to two times, unless a deadline was already postponed.
Collaboration
No collaboration is permitted on assignments.
Final exam
The exam is closed book; a simple calculator and photo ID are allowed or required, respectively.
AI tools
AI tools cannot be used to demonstrate learning outcomes; project use requires instructor approval and documentation.
Course materials
Do not submit instructor-provided assignments, lecture notes, or similar materials to third-party sites.

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