The goal is to introduce students to modern and extremely useful topics in computational statistics. It focuses on computational aspects and provides a hands-on introduction to fundamental concepts of data analysis. The course is composed of 3 hours lecture and 2 hours lab with programming assignments in Matlab. Consequently, the students will be able to immediately see their results with programming assignments in Matlab. No prior Matlab knowledge is required. The course offers a solid foundation for further courses in data mining, machine learning, artificial intelligence, robotics, computer vision, and in general in computational statistics and scientific computing.

For any CIS prerequisite course taken prior to Spring 2012 a grade of C or better is required.
Credit Hours: 4.000

Levels: Graduate, Undergraduate
Schedule Types: Lecture and Lab

Division: Undergraduate
Department: CST:Computer & Info Sci

General Requirements:
(  Course or Test: CIS 1068 | Minimum Grade of C- | May not be taken concurrently.  )
OR
(  Course or Test: CIS 1073 | Minimum Grade of C- | May not be taken concurrently.  )
AND (  Course or Test: MATH 1041 | Minimum Grade of C- | May not be taken concurrently.  )
OR
(  Course or Test: MATH 1022 | Minimum Grade of C- | May not be taken concurrently.
AND Course or Test: MATH 1031 | Minimum Grade of C- | May not be taken concurrently.  )
OR
(  Course or Test: MATH 1941 | Minimum Grade of C- | May not be taken concurrently.  )
OR
(  Course or Test: MATH 1042 | Minimum Grade of C- | May be taken concurrently.  )
OR
(  Course or Test: MATH 1942 | Minimum Grade of C- | May be taken concurrently.  )
OR
(  Course or Test: MATH 1951 | Minimum Grade of C- | May be taken concurrently.  )
OR
(  Course or Test: MATH 2043 to 3080 | Required Courses: 1 | Minimum Grade of C- | May be taken concurrently.  )
OR
(  MA05 Y - May not be taken concurrently.  )
OR
(  MA06 Y - May not be taken concurrently. )