Course Information

Course Name	Turkish	Büyük Çaplı Veri İşleme
	English	Large Scale Data Processing
Course Code	BLU 605E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Behçet Uğur Töreyin
Course Objectives		The aim of the course is to teach techniques on (stochastic) convex optimization and sparse representations based on probability theory and linear algebra in order to process large scale data.
Course Description		Course contents are as follows: • probability theory (2 weeks), • linear algebra (2 weeks), • convex optimization (4 weeks), • sparse representation methods (4 weeks) • large scale data processing applications (2 weeks).
Course Outcomes		-
Pre-requisite(s)		Probability theory and linear algebra at the undergraduate level.
Required Facilities		-
Other		-
Textbook		• Sparse and redundant representations : from theory to applications in signal and image processing / Michael Elad, Springer, 2010.
Other References		• Goodman, Yates, “Probability and Stochastic Processes, A friendly introduction for Electrical and Computer Engineers,” Third Ed., Wiley. • Montgomery, Runger, “Applied Statistics and Probability for Engineers,” Sixth Ed., Wiley. • Strang, “Linear Algebra and Its Applications,” Second Ed., Academic Press. • Boyd, Vandenberghe, “Convex Optimization,” Cambridge University Press.