Course Information

Course Name	Turkish	Temel Bilimlerde Veri Analizi
	English	Data Analysis in Fund.Sciences
Course Code	MAT 388E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	-	-	-
Course Language		English
Course Coordinator		Atabey Kaygun Atabey Kaygun
Course Objectives		To teach undergraduate mathematics majors how to use fundamental machine learning and statistical models in prediction problems based on data, interpreting the results of the machine learning and statistical models they are going to develop, writing analytical reports helping decision making processes.
Course Description		Best practices in data analysis. Basic R. Basic python. Basic statistics. Univariate and multivariate data problems. Boolean decision problems. Discrete Decision problems. Unsupervised clustering models. Neural network models.
Course Outcomes		A student who finished this course successfully will I. gain a basic understanding of main problems in data analysis, II. gain an operational knowledge on how to use basic tools of statistics and machine learning in data analysis problems III. learn how to write simple analytical reports on the machine learning and statistical models they develop in this class.
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