Akademik Dersler - Tanıtım

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

Language of Instruction	Türkçe
Course Type	Elective Courses
Course Instructor(s)	DR. ÖĞR. ÜYESİ BAŞAK ERDEM KARA
Mode of Delivery	Distance Learning
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 Reading List	Lesmeister, C. (2019) Mastering Machine Learning with R. Gürsakal, N. (2017). Makine Öğrenmesi ve Dersin Öğrenme.
Assessment methods and criteria	Homework and Classical Exam.
Work Placement	There is no work placement in this course.
Catalog Content	Fundamentals of Machine Learning: Applications of ML in different fields, Training set, Test set; Fundamentals of R Language: Basic concepts, Data types and structures, Data frames, Exporting and Importing data; Classification: K-nearest neighbour, Decision trees, Neural networks; Regression: Simple linear regression, Multiple regression, Neural networks; Clustering: K-means, Hierarchical clustering; Ensemble Learning: Evaluating models, Random forest; Deep Learning: Deep neural networks.