Introduction to Artificial Intelligence

Објавено: June 28, 2022
1. Course Title Introduction to Artificial Intelligence
2. Code 4ФЕИТ01З013
3. Study program КСИАР
4. Organizer of the study program (unit, institute, department) Faculty of Electrical Engineering and Information Technologies
5. Degree (first, second, third cycle) First cycle
6. Academic year/semester III/5 7. Number of ECTS credits 6
8. Lecturer D-r Vesna Ojleska Latkoska
9. Course Prerequisites Passed: Programming and Аlgorithms
10. Course Goals (acquired competencies): Introduction to artificial intelligence. Acquiring skills for autonomously solving practical engineering problems in the field of artificial intelligence.
11. Course Syllabus: 1. Introduction to Artificial Intelligence (AI). 2. Intelligent agents and their environment. 3. Problem solving in AI: problem formulation in AI, measure of success of the solution of a problem in AI, notion of blind and heuristic, non-optimal and optimal search, different procedures for blind search, heuristic search procedures, problems with constraints – definition, procedure, examples. 4. Games in AI: notion of optimal decision making in games, notion of optimal strategies in games, function for estimating positions in games, MINIMAX algorithm, multiplayer games, alpha-beta trimming, games of chance. 5. Learning: forms of learning, learning trees, statistical learning methods, application in playing games, application in robotics. 6. Neural networks: structure of neural networks, types of neural networks and their training.
12. Learning methods: Combined way of learning: lectures, supported by presentations, homework and auditory exercises, as well as practical laboratory exercises.
13. Total number of course hours 2 + 2 + 1 + 0
14. Distribution of course hours 180
15. Forms of teaching 15.1. Lectures-theoretical teaching 30
15.2. Exercises (laboratory, practice classes), seminars, teamwork 45
16. Other course activities 16.1. Projects, seminar papers 10
16.2. Individual tasks 10
16.3. Homework and self-learning 85
17. Grading 17.1. Exams 5
17.2. Seminar work/project (presentation: written and oral) 10
17.3. Activity and participation 5
17.4. Final exam 80
18. Grading criteria (points) up to 50 points 5 (five) (F)
from 51to 60 points 6 (six) (E)
from 61to 70 points 7 (seven) (D)
from 71to 80 points 8 (eight) (C)
from 81to 90 points 9 (nine) (B)
from 91to 100 points 10 (ten) (A)
19. Conditions for acquiring teacher’s signature and for taking final exam Regular attendance to the lectures and exercises, as well as successful and timely completion of all laboratory exercises.
20. Forms of assessment Two partial written exams are scheduled (at the middle and at the end of the semester, each with duration of 120 minutes), tests that are conducted during the classes, as well as homework and project assignments, which are presented/defended during the semester.
1. Students who have passed the partial exams are considered to have passed the final written exam. A final oral exam can also be scheduled, with duration up to 60 minutes. The final grade is formed based on the points from the partial written exams, the tests, the homework and the project assignments and the final oral exam (if scheduled).
2. In the planned exam sessions, a final written exam is taken (lasting 120 minutes). For students who have passed the final written exam, a final oral exam can also be scheduled (with duration up to 60 minutes). The final grade is formed based on the points from the final written exam, the tests, the homework and the project assignments and the final oral exam (if scheduled).
21. Language Macedonian and English
22. Method of monitoring of teaching quality Internal evaluation and surveys.
23. Literature
23.1. Required Literature
No. Author Title Publisher Year
1 Stuart Russell, Peter Norvig Artificial Intelligence A Modern Approach, Fourth Edition Pearson education limited 2021
23.2. Additional Literature
No. Author Title Publisher Year
1 Elizabeta Lazarevska Lecture Notes for Machine Learning FEEIT, UKIM 2017
2 Elizabeta Lazarevska Collection of Solved Problems in Artificial Intelligence UKIM 2020