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. ÇAĞLA TUĞBERK ARIKER
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	Define the theories, concepts and principles of the basic and sub-fields of business.
2	Explain business functions and processes based on current scientific sources.

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Relate internationally valid business cases with the theories and concepts of other social sciences.

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Explain the current events and facts in his / her field analytically and systematically based on advanced knowledge and skills he / she has.

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use the theoretical and factual knowledge in business for occupational practices.
2	Solve individual and organizational problems in business life.
3	Use computer programs (SPSS, R, Excel, Stata) efficiently against the complex business problems.

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Plan research and work using knowledge and skills gained in the field of business.
2	Organize the activities for organizational goals and purposes independently.

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Criticize advanced knowledge and skills in the field with a critical approach.
2	Develop the existing knowledge and skills with a critical point of view under the impact of scientific, technological and current developments.

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Express his/her knowledge, thoughts and solutions on business to related stakeholders in written and verbal ways.
2	Use the information and communication technology software and equipment required for business.

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Apply the social, scientific, cultural and ethical values at the stages of the collection of data, their implementation, interpretation and announcement of results in the field of business.
2	Relate the concepts of social rights, occupational safety, employee health, quality management and sustainability with the cases in business life.

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