Akademik Dersler - Tanıtım

Last Updated: 21/07/2026

Code - Course Title	Course Type	Laboratory + Practice	ECTS
VBA301 - Machine Learning II: Unsupervised Learning	V. SEMESTER	3 +1	6.0

Language of Instruction	İngilizce
Course Type	Required Courses
Course Instructor(s)	ARAŞ. GÖR. DR. ÖNDER DORAK
Mode of Delivery	Face to face
Place of Delivery
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Work Placement
Aims of the Course

Weeks	Learning Outcomes	Topics	Teaching Methods
Week - 1		Unsupervised Learning: Pattern discovery concepts
Week - 2		Clustering concepts overview
Week - 3		Clustering algorithms: Implementing k-means and k-medoids
Week - 4		Hierarchical clustering methodologies
Week - 5		Density-based spatial clustering (DBSCAN)
Week - 6		Dimensionality Reduction: PCA theory
Week - 7		PCA application and t-SNE for visualization
Week - 8		UMAP and Factor analysis
Week - 9		Association Rules: The Apriori algorithm
Week - 10		Market basket analysis
Week - 11		Evaluating support/confidence/lift parameters
Week - 12		Building fundamental recommendation systems
Week - 13		Anomaly Detection: Identifying outliers
Week - 14		Isolation forests, One-class SVMs, Fraud detection

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Assessment Method and Passing Requirements
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