PERFORMING ARTS
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
CMP4501	Introduction to Artificial Intelligence and Expert Systems	Spring Fall	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Dr. Öğr. Üyesi TEVFİK AYTEKİN
Recommended Optional Program Components:	None
Course Objectives:	The course introduces basics of artificial intelligence. Basic search techniques used for problem solving, fundamentals of knowledge representation and logical formalisms, basic learning algorithms, and fundamentals of expert systems will be introduced.

Learning Outcomes

The students who have succeeded in this course;
I. Be able to formulate a state space description of a problem
II. Be able to select and implement brute-force or heuristic algorithm for a problem.
III. Be able to implement minimax search with alpha-beta pruning.
IV. Be able to compare and evaluate the most common models for knowledge representation.
V. Be able to explain the operation of the resolution technique for theorem proving.
VI.Be able to explain the differences among supervised and unsupervised learning.
VII. Be able to explain the concepts of overfitting, underfitting, bias, and variance.
VIII. Be able to implement some of the basic algorithms for supervised learning and unsupervised learning.
IX. Be able to describe fundamentals of expert systems and evaluate them.

Course Content

Introduction to AI, state spaces and searching, heuristic functions and search, alpha-beta pruning, propositional and first-order predicate logic, propositional and first order inference, unification and resolution, linear regression, logistic regression, neural networks and backpropagation algorithm, Bayes’ rule and naive Bayes algorithm, clustering and k-means algorithm, fundementals of expert systems, software for expert systems.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to AI
2)	State spaces and searching.
3)	Heuristic functions and search
4)	Decisions in games, alpha-beta pruning.
5)	Propositional and first-order predicate logic
6)	Propositional and first order inference
7)	Unification and resolution
8)	Linear Regression
9)	Midterm
10)	Logistic Regression
11)	Neural networks and backpropagation algorithm.
12)	Bayes’s rule and naive Bayes algorithm.
13)	Clustering and k-means algorithm
14)	Fundementals of expert systems.
15)	Software for expert systems.

Sources

Course Notes / Textbooks:	Russell, S., Norvig, P., Artificial Intelligence: A Modern Approach, (3rd edition), 2009. Giarratano, J.C., Riley, G.D., Expert Systems: Principles and Programming, (4th edition), 2004.
References:	Yok - None

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	2	% 10
Project	1	% 20
Midterms	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	42
Project	4	20
Homework Assignments	10	20
Quizzes	2	8
Midterms	5	15
Final	5	20
Total Workload		125

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	They acquire theoretical, historical and aesthetic knowledge specific to their field by using methods and techniques related to performing arts (acting, dance, music, etc.).	2
2)	They have knowledge about art culture and aesthetics and they provide the unity of theory and practice in their field.	2
3)	They are aware of national and international values in performing arts.	2
4)	Abstract and concrete concepts of performing arts; can transform it into creative thinking, innovative and original works.	1
5)	They have the sensitivity to run a business successfully in their field.	3
6)	Develops the ability to perceive, think, design and implement multidimensional from local to universal.	3
7)	They have knowledge about the disciplines that the performing arts field is related to and can evaluate the interaction of the sub-disciplines within their field.	2
8)	They develop the ability to perceive, design, and apply multidimensionality by having knowledge about artistic criticism methods.	3
9)	They can share original works related to their field with the society and evaluate their results and question their own work by using critical methods.	1
10)	They follow English language resources related to their field and can communicate with foreign colleagues in their field.	1
11)	By becoming aware of national and international values in the field of performing arts, they can transform abstract and concrete concepts into creative thinking, innovative and original works.	3
12)	They can produce original works within the framework of an interdisciplinary understanding of art.	2
13)	Within the framework of the Performing Arts Program and the units within it, they become individuals who are equipped to take part in the universal platform in their field.	3
14)	Within the Performing Arts Program, according to the field of study; have competent technical knowledge in the field of acting and musical theater.	2
15)	They use information and communication technologies together with computer software that is at least at the Advanced Level of the European Computer Use License as required by the field.	3