Intelligent Systems

1.

Subject title

Intelligent Systems

Интелигентни системи

2.

Code

F23L3S107

3.

Study program

Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Информатичка едукација, Software engineering and information systems, Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Software engineering and information systems, Стручни студии за програмирање, Стручни студии за програмирање, Bioinformatics, Software Engineering,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Прв циклус

6.

Academic year / semester

4 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Ана Мадевска Богданова

9.

Prerequisites for enrollment

Вештачка интелигенција или Вовед во науката за податоци или Машинско учење

10.

Subject goals and competencies:

The aim of the course is to complete the students` knowledge in the field of intelligent systems, starting from data preprocessing to validating the built system. Students will be able to build an intelligent system from start to finish on real problems from a specific domain, using platforms for automatization of the building IS processes.

11.

Subject 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); Discriminative versus generative methods for building IS; Fast Fourier transform, time and space domain; Transferred learning; Interpretation of built models - Shapley value Processing of a real problem – methods for the best selection of techniques for preprocessing, model construction, evaluation and interpretation of built IS; Processing a real problem – designing an IS for a chosen domain and its evaluation and interpretation.

12.

Learning methods:

Предавања со користење на презентации, интерактивни предавања, вежби (користење на опрема и софтверски пакети), тимска работа, пример случаи, поканети гости предавачи, самостојна изработка и одбрана на проектна задача и семинарска работа.

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

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

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

45 hours

16.

Other forms of activities

16.1.

Project tasks

15 hours

16.2.

Independent tasks

15 hours

16.3.

Homework

75 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

15 points

17.3.

Activities and learning

10 points

17.4.

Final exam

20 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.

Condition for signature and taking final exam

Реализирани актибвности 15.2 и 16.1

20.

Language of instruction

Македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature