Subject

Natural language processing

Course Title

Natural language processing
Natural language processing

Code

F18L3W142

Study Programme

—

Organizer of the study programme (unit, institute, department or division)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

First Cycle

Academic year / semester

7 / Winter

Number of ECTS credits

Teacher

—

Prerequisites for enrolling in the course

Machine learning

10.

Objectives of the course programme (competences)

The goal of the course is for students to acquire the basic theoretical and practical knowledge of natural language processing algorithms. They will acquire knowledge of how linguistic structure and meaning are represented in data structures, how these structures and meanings are recognized in textual data, and, most importantly, how to build algorithms that will identify the correct answers among a large number of options.

11.

Course content

Introduction; Basic Text Processing; Morphology; Syntax, Semantics, and Ambiguity of Natural Languages; Word Morphology and Finite Automata; Modeling Natural Languages; Basic Algorithms for Spelling Correction; Word Stemming; Parsing; Text Classification; Fundamentals of Machine Translation; Basic Algorithms for Information Extraction from Text Data;

12.

Learning methods

Lectures supported by slide presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, guest lecturers, independent preparation and defense of a project assignment and a seminar paper, and learning in an electronic environment (forums, consultations).

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	30 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	45 hours

16.

Other forms of activities

16.1.	Project assignments	15 hours
16.2.	Independent assignments	15 hours
16.3.	Home study	75 hours

17.

Assessment method

17.1.	Tests	10 points
17.2.	Seminar paper / project (presentation: written and oral)	15 points
17.3.	Activities and learning	10 points
17.4.	Final exam	70 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirement for obtaining a signature and taking the final exam

completed activities 15.1 and 15.2

20.

Language of instruction

Macedonian and English

21.

Method for monitoring the quality of teaching

internal evaluation and survey mechanism

22.

Literature

22.1.	Required literature No. Author Title Publisher Year
22.2.	Additional literature No. Author Title Publisher Year