| 1. | Course Title | Artificial Intelligence | |||||||||||
| 2. | Code | 4ФЕИТ01003 | |||||||||||
| 3. | Study program | 6-ARSI | |||||||||||
| 4. | Organizer of the study program (unit, institute, department) | Faculty of Electrical Engineering and Information Technologies | |||||||||||
| 5. | Degree (first, second, third cycle) | Second cycle | |||||||||||
| 6. | Academic year/semester | I/1 | 7. | Number of ECTS credits | 6.00 | ||||||||
| 8. | Lecturer | Dr Vesna Ojleska Latkoska | |||||||||||
| 9. | Course Prerequisites | ||||||||||||
| 10. | Course Goals (acquired competencies):
To master the advanced concepts of artificial intelligence and to be able to implement the acquired knowledge in different technical and non technical fields. |
||||||||||||
| 11. | Course Syllabus:
Introduction: Artificial intelligence and agents, designing agents, agent design space, prototypical applications. Agent architectures and hierarchical control: agents, agent systems, hierarchical control, acting with reasoning. Reasoning with certainty: searching for solutions, reasoning with constraints, propositions and interference. Planning with certainty: representing states, actions and goals, forward planning, regression planning, planning as CSP, partial-order planning. Learning with certainty: supervised machine learning, basic models, overfitting, neural networks and deep learning. |
||||||||||||
| 12. | Learning methods:
Slide presentations, interactive lectures, exercises (use of equipment and software), teamwork, case studies, invited guest lecturers, independent preparation and defense of project and seminar work, learning in digital environment (forums, consultations). |
||||||||||||
| 13. | Total number of course hours | 180 | |||||||||||
| 14. | Distribution of course hours | 3 + 3 | |||||||||||
| 15. | Forms of teaching | 15.1 | Lectures-theoretical teaching | 45 hours | |||||||||
| 15.2 | Exercises (laboratory, practice classes), seminars, teamwork | 45 hours | |||||||||||
| 16. | Other course activities | 16.1 | Projects, seminar papers | 30 hours | |||||||||
| 16.2 | Individual tasks | 30 hours | |||||||||||
| 16.3 | Homework and self-learning | 30 hours | |||||||||||
| 17. | Grading | ||||||||||||
| 17.1 | Exams | 0 points | |||||||||||
| 17.2 | Seminar work/project (presentation: written and oral) | 50 points | |||||||||||
| 17.3. | Activity and participation | 0 points | |||||||||||
| 17.4. | Final exam | 50 points | |||||||||||
| 18. | Grading criteria (points) | 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. | Conditions for acquiring teacher’s signature and for taking final exam |
Successfully completed project assignment. |
|||||||||||
| 20. | Forms of assessment |
The students are obliged to complete and present a project assignment during the semester. A final written and/or oral exam is scheduled during the exam sessions. The students complete the course if they pass the final exam and had previously completed and presented the project assignment during the semester. The final grade takes into account the points from both the final exam and the project assignment. |
|||||||||||
| 21. | Language | Macedonian and English | |||||||||||
| 22. | Method of monitoring of teaching quality | Self-evaluation | |||||||||||
| 23. | Literature | ||||||||||||
| 23.1. | Required Literature | ||||||||||||
| No. | Author | Title | Publisher | Year | |||||||||
| 1. | David L. Poole, Alan K. Mackworth | Artificial Intelligence: Foundations of Computational Agents | Cambridge University Press | 2017 | |||||||||
| 23.2. | Additional Literature | ||||||||||||
| No. | Author | Title | Publisher | Year | |||||||||
| 1. | Stuart Russell, Peter Norvig | Artificial Intelligence: A Modern Approach | Pearson Education | 2015 | |||||||||
