Course Information

Course Name	Turkish	Veri Bilimi ve Makine Öğrenmesi Uygulamaları
	English	Apply.Data Sci.&Mach. Learning
Course Code	ARC 401E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Aslı Kanan
Course Objectives		1. Introducing the general approach of AI and ML 2. Giving knowledge about the architectural data 3. Examining different data types and procedures, data annotation 4. Feature extraction, correlation between input and output
Course Description		Artificial intelligence (AI) is the application of simulating human intelligence to machines, which makes them think and act like humans beings and therefore imitate people’s actions. Machine learning (ML) is a branch of AI, which uses algorithms to find patterns in large datasets and create predictions accordingly. In one way, AI and ML technologies reconstruct professional practices. This course will use significant examples from architecture to cover major machine learning tasks including regression, classification and clustering. Built environment data will be used for better decisions and predictions. Data driven design, data analysis and interpretation will be elaborated. Lectures will both cover the fundamental computational explanations and architecture based cases regarding to specific machine learning algorithms.
Course Outcomes
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