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Course Details

Fall 2018-2019
ORF 350 (QR)   na, npdf

Analysis of Big Data

Krishnakumar Balasubramanian

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

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, ORF 309.

Other information:
R programming.

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
20456 L01 11:00:00 am - 12:20:00 pm T Th        Enrolled:0 Limit:0 Canceled