Modern intelligent systems

1.

Subject title

Modern intelligent systems

Современи интелигентни системи

2.

Code

IS-Z-03

3.

Study program

Inteligent Systems, Cloud Computing, IT management, Bioinformatics, Data science in computer science and engineering, Security, Cryptography and Coding, Еducation with ICT, Eco-informatics, Internet Technologies and cyber security, Computer Science, Software for embedded systems, Software Engineering, Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Software Engineering, Statistics and Data Analytics, Statistics and Data Analytics,

4.

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

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Зимски

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Андреа Кулаков проф. д-р Георгина Мирчева проф. д-р Миле Јованов проф. д-р Невена Ацковска

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

The aim of this course is for the student to gain a perspective on intelligent systems and their impact on processes in industry, healthcare, education and science. Students will learn the modern applications and trends in the development of intelligent systems, such as recognition of persons and objects, autonomous vehicles, machines that resonate like humans, smart environments in the age of the Internet of Things, etc. The students will get acquainted with the diversity of modern intelligent systems, which have the ability to extract and preserve knowledge. They will learn the reasoning processes that occur in these systems. They will be able to use intelligent systems that learn from their experience and training, are able to deal with imprecise expressions and facts, and find solutions through processes that are similar to natural evolution. The technologies and algorithms that make this possible are also the goal of this course.

11.

Subject content:

A historical overview of the development of intelligent systems. Problems and their solution. Modern knowledge and reasoning systems. Reasoning with the concept of possibility and probability. Modern games. Intelligent speech and image recognition systems. Architectures of intelligence. Deep learning. Robotic Intelligent Systems. Smart environments. ICT legislation, regulations and cyber laws for intelligent systems. Challenges and future trends in IS.

12.

Learning methods:

Предавања поддржани со презентации преку слајдови, 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, учење во електронско опкружување (форуми, консултации).

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

60 + 0 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

60 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

0 hours

16.

Other forms of activities

16.1.

Project tasks

45 hours

16.2.

Independent tasks

45 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

15 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

15 points

17.4.

Final exam

0 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 активности 15.1 и 15.2

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