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Course Details

Spring 2015-2016
ORF 350 (QR)   No Audit

Analysis of Big Data

Han Liu

The amount of data in our world has been exploding, and analyzing large data sets is becoming a central problem in our society. This course introduces the statistical principles and computational tools for analyzing big data: the process of exploring and predicting large datasets to find hidden patterns and gain deeper understanding, and of communicating the obtained results for maximal impact. Topics include massively parallel data management and data processing, model selection and regularization, statistical modeling and inference, scalable computational algorithms, descriptive and predictive analysis, and exploratory analysis.

Sample reading list:
Professor Han Liu, Lecture Notes

Reading/Writing assignments:
Programming assignments

Requirements/Grading:
Mid Term Exam - 10%
Take Home Final Exam - 10%
Programming Assignments - 60%
Class/Precept Participation - 20%

Other Requirements:
Statistical, design or other software use required
Open to Juniors and Seniors Only.

Prerequisites and Restrictions:
ORF 245.

Other information:
R programming

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
41078 L01 11:00 am - 12:20 pm T Th   Friend Center   006   Enrolled:86 Limit:85 Closed