IntroNLP

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Middle East Technical University

Computer Engineering Department

CENG 463 Introduction to Natural Language Processing

FALL 2025-2026

Instructor:

Asst. Prof. Çağrı Toraman (ctoraman@metu.edu.tr)

Office: B208

TA:

Aslı Umay Öztürk (asozturk@metu.edu.tr)

Office: B109

Time:

Tuesday, 11:40 - 13:30

Wednesday, 11:40 - 12:30

Room:

BMB-4

Course Objectives:

The primary objective of this course is to introduce students how to design, develop, and deploy systems that can extract insights and meaning from human language data. Students will be able to analyze text datasets, work with popular Natural Language Processing (NLP) libraries, and apply NLP techniques to solve real-world problems. Through lectures, discussions, and hands-on programming assignments, students will gain a deep understanding of underlying structure of state-of-the-art NLP algorithms and models.

Background Requirements:

5710280 FORMAL LANGU.AND ABSTRACT MACHINES (required);

Python programming skills (strongly recommended).

Course Slides:

Will be published at ODTUClass. Will be here at the end of semester.

Textbook:

D. Jurafsky and J. H. Martin. 2023. “Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition” (Third edition).

Grading (Tentative):

Programming Assignment: 18% (5-5-8)

Quiz: 20% (6-6-8)

Midterm Exam: 25%

Final Exam: 30%

Active Participation: 7%

Course Outline(Tentative):

Exam Details:

Midterm and Final will be written exams that involve multiple questions types including but not limited to true-false, short answer, and computational questions.

Programming Assignment Details:

There will be 3 programming assignments to improve your programming skills on Natural Language Processing. They will be published at ODTUClass, and must be completed individually.

First assignment will be possibly related to regular expressions, n-grams, and bag-of-words. Second assignment will be possibly related to word embeddings and neural models. Third assignment will be possibly related to large language models.

Quiz Details:

There will be 3 quizzes. Each quiz will target to evaluate your knowledge and skills on 2 topics: (1) previously discussed lecture topics, and (2) last submitted programming assignment.

Active Participation:

In-class participation means not necessarily attendance but interactive participation such as asking questions, answering questions, commenting on course material.

Late Submission Policy:

You will have 2 more days for late submissions. However, 10 points will be deducted for each 24 hours.

Generative AI Policy:

You may use AI assistants for learning and asking questions; but you are forbidden to copy/paste code.