Akademik Dersler - Tanıtım

Last Updated: 30/09/2026

Code - Course Title	Course Type	Laboratory + Practice	ECTS
ÖVA509 - Introduction to Machine Learning with R	I. SEMESTER	3 +0	6.0

Language of Instruction	Türkçe
Course Type	Elective Courses
Course Instructor(s)	DOÇ. DR. BAŞAK ERDEM KARA
Mode of Delivery	Distance Learning
Place of Delivery
Used Educational Platforms
Prerequisites	Participants are expected to have the basic knowledge and use skills about R Programming Language.
Courses Recomended	Participants are advised to take the course \\\"Introduction to Statistics in Social Sciences with R in the AKADEMA platform.
Recommended Resources	Lesmeister, C. (2019) Mastering Machine Learning with R. Gürsakal, N. (2017). Makine Öğrenmesi ve Derin Öğrenme.
Work Placement	There is no work placement in this course.
Aims of the Course

Weeks	Learning Outcomes	Topics	Teaching Methods
Week - 1		Fundamentals of Machine Learning
Week - 2		Applications of Machine Learning
Week - 3		Training and Test Data
Week - 4		R Programming Language
Week - 5		Classification: k-nearest neighbours, Decision Trees
Week - 6		Classification: Decision Trees
Week - 7		Classification: Artificial Neural Networks
Week - 8		Simple Linear Regression and Multiple Regression
Week - 9		Classification and Regression-Based R Applications
Week - 10		Clustering: K-means and Hierarchical Clustering
Week - 11		Evaluation of Models
Week - 12		Random Forest
Week - 13		R Applications
Week - 14		Deep Learning

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Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	40
Final Exam	1	60
Toplam (%)		100