Subject

Intelligent systems

Course Title

Intelligent systems
Intelligent systems

Code

F18L3S107

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

8 / Summer

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 to round out students' knowledge in the field of intelligent systems, from data preprocessing to validating the built system. Students will be equipped to develop an intelligent system from start to finish for real-world problems in a specific domain.

11.

Course content

Overview of the domains in which modern intelligent systems are used; Modern techniques for data preprocessing; Modern techniques from machine learning and deep learning for building IS models; Evaluation of IS models (classification and regression); Discriminant versus generative methods for building IS; Fast Fourier Transform, time and spatial domain; Transfer learning; Interpretation of built models - Shapley value. Real-world problem processing – methods for the optimal selection of techniques for preprocessing, model building, evaluation, and interpretation of the built IS; Real-world problem processing – designing an IS for a selected domain and its evaluation and interpretation.

12.

Learning methods

Lectures using presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, guest lectures, independent preparation and defense of a project assignment and a seminar paper.

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	50 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

Activities 15.2 and 16.1 have been completed.

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