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Course Details

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

Analysis of Big Data

Miklos Z. Racz

The amount of data in our world has been exploding and analyzing large data sets is a central challenge in society. This course introduces the statistical principles and computational tools for analyzing big data. Topics include statistical modeling and inference, model selection and regularization, scalable computational algorithms, and more.

Sample reading list:
Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elements of Statistical Learning (Second Edition)

Reading/Writing assignments:
Programming assignments

Requirements/Grading:
Mid Term Exam - 20%
Take Home Final Exam - 30%
Programming Assignments - 50%

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

Prerequisites and Restrictions:
ORF 245, ORF 309.

Reserved Seats:
Open to ORF Juniors Only 20
Open to ORF Seniors Only 20

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
40390 L01 08:30:00 am - 09:50:00 am M W        Enrolled:55 Limit:80
42473 P01 03:30:00 pm - 04:20:00 pm T        Enrolled:24 Limit:27
42474 P02 07:30:00 pm - 08:20:00 pm T        Enrolled:21 Limit:27
42475 P03 07:30:00 pm - 08:20:00 pm Th        Enrolled:10 Limit:27