19D111VIE - Artificial Intelligence and Expert Systems

Course specification
Course title		Artificial Intelligence and Expert Systems
Acronym		19D111VIE
Study programme		Electrical Engineering and Computing
Module		Computer Engineering and Informatics
Type of study		doctoral studies
Lecturer (for classes)		professor PhD Boško Nikolić professor PhD Dražen Drašković
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB		9.0	Status	elective
Condition
The goal		Introduce students to the methodologies and applications of modern development in artificial intelligence area, with an emphasis on advanced technologies.
The outcome		The learning outcomes of the course are to enable students to implement various concepts and technologies in artificial intelligence applications. They are able to identify characteristics of the system and select the best and most effective solutions.
Contents
Contents of lectures		Knowledge and reasoning - BPN, Rules, semantics and reasoning in Bayes's network; decision support - the basis of the theory model; working with multiple agents, game theory. Machine learning - forms of learning, decision trees, machine learning theory. Effective interpretation, search and processing of a data set. NLP - semantic similarity, sentiment.
Contents of exercises
Literature
S. Russel, P. Norvig - Artificial Intelligence - A Modern Approach (Original title) Daniel Jurafsky, James H. Martin: Speech and Language Processing (Original title) Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal: Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann. (Original title)
Number of hours per week during the semester/trimester/year
Lectures	Exercises	OTC	Study and Research	Other classes
8
Methods of teaching		Presentation, individual work, discussion
Knowledge score (maximum points 100)
Pre obligations		Points	Final exam	Points
Activites during lectures		0	Test paper	0
Practical lessons		0	Oral examination	30
Projects		70
Colloquia		0
Seminars		0