ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
YBS414	ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING	5	3	3	5

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Elective
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assoc.Prof. SARP BAĞCAN
Instructor(s) of the Course Unit
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	The aim of the course is to provide an introduction to the current status of Artificial Intelligence and Machine Learning.
Contents of the Course Unit:	The content of the course is to create awareness in the field of Artificial Intelligence and Machine Learning and to learn algorithms with examples on current topics.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Defines the concepts of artificial intelligence and machine learning. Discovers current topics and content in this field. Examines how a business can develop projects in this field. Masters the algorithms in its field. Can take part in studies in this field.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	Literature Reading, Current Examples	Artificial Intelligence, Introduction to Python	Explanation, Discussion, Application
2	Literature Reading, Current Examples	Machine Learning, Data and Data Preprocessing Concepts	Explanation, Discussion, Application
3	Literature Reading, Current Examples	Data Preprocessing Concepts and Python	Explanation, Discussion, Application
4	Literature Reading, Current Examples	Data Preprocessing with Python (Seaborn Library)	Explanation, Discussion, Application
5	Literature Reading, Current Examples	Data Preprocessing and Visualization with Python (Pandas and MatplotLib Libraries)	Explanation, Discussion, Application
6	Literature Reading, Current Examples	Linear Regression	Explanation, Discussion, Application
7	Literature Reading, Current Examples	Linear Regression (coding)	Explanation, Discussion, Application
8	-	MID-TERM EXAM	-
9	Literature Reading, Current Examples	Decision Trees	Explanation, Discussion, Application
10	Literature Reading, Current Examples	Decision Trees (coding)	Explanation, Discussion, Application
11	Literature Reading, Current Examples	Random Forest	Explanation, Discussion, Application
12	Literature Reading, Current Examples	Logistic Regression	Explanation, Discussion, Application
13	Literature Reading, Current Examples	Support vector machine	Explanation, Discussion, Application
14	Literature Reading, Current Examples	Artificial Neural Networks	Explanation, Discussion, Application
15	Literature Reading, Current Examples	Artificial Neural Networks	Explanation, Discussion, Application
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Makine öğrenmesi / Ethem Alpaydın Veri madenciliği ve makine öğrenmesi : temel kavramlar, algoritmalar, uygulamalar / editörler. M. Erdal Balaban, Elif Kartal.

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description	Examination Method
Mid-Term Exam	1	50
Final Exam	1	50
TOTAL	2	100

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Describe basic communication theories with the knowledge gained in public relations and publicity.
2	List the main features of communication in items.
3	Interpret the basic characteristics of communication and create a creative solution to ensure reconciliation in an existing communication problem.

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use the basic information in the field of Public Relations and Publicity in interdisciplinary studies.
2	Evaluate the knowledge related to social and natural sciences and produce projects in professional life.
3	Tell the basic concepts of public relations and advertising in detail.

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Analyze and evaluate social events at national and international level in the light of current debates.
2	Use the leadership, communication and presentation skills in occupational events.

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Follow the innovations in the field of communication and important written and oral communication tools related to the field.
2	Write press releases for the purpose of introducing the institution he/she works at or owns.
3	Create communication programs within the public relations and advertising campaign.

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use published domestic and foreign data sources related to public relations and advertising in the field of communication and communication area in his / her own works such as articles and projects.

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Evaluate the planning processes of past communication programs, public relations and advertising practices.

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use communication techniques in the right place, environment and time.

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Plan communication programs in the awareness of ethical values in the professional work.

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	14	1	14
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	0	0	0
Assignment (Homework)	7	7	49
Project Work	1	14	14
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	1	1
Preparation for the Final Exam	2	2	4
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	0	0	0
Short Exam	2	2	4
Preparation for the Short Exam	0	0	0
TOTAL	42	0	129