Artificial Intelligence

1.

Subject title

Artificial Intelligence

Вештачка интелигенција

2.

Code

F23L2S030

3.

Study program

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

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

2 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Андреа Кулаков проф. д-р Георгина Мирчева доц. д-р Илинка Иваноска проф. д-р Кире Триводалиев ворн. проф. д-р Петре Ламески проф. д-р Соња Гиевска

9.

Prerequisites for enrollment

Освоени најмалку 36 ЕКТС

10.

Subject goals and competencies:

The successful student will have in-depth knowledge of the fundamental areas of artificial intelligence, including: search, problem solving, knowledge representation, reasoning, decision making, planning and learning and their application. It will also be able to design and realize key problems from intelligent systems of medium complexity and evaluate their behavior.

11.

Subject content:

Lectures: 1. About artificial intelligence About intelligent agents 2. Introduction to the search Uninformed search 3. Informed search 4. Fulfillment of conditions 5. Adversarial search 6. Genetic algorithms 7. Probabilistic reasoning Bayesian networks 8. Fundamentals of Machine Learning Naive Bayesian algorithm 9. Perceptron 10. Decision trees 11. Neural networks 12. Areas of application of artificial intelligence Natural language processing, machine vision, robotics

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 + 60 + 15 + 15 + 60 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

60 hours

16.

Other forms of activities

16.1.

Project tasks

15 hours

16.2.

Independent tasks

15 hours

16.3.

Homework

60 hours

17.

Grading method

17.1.

Tests

40 points

17.2.

Seminar work / 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.

Condition for signature and taking final exam

Реализирани активности 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