University of Connecticut University of UC Title Fallback Connecticut

Big Data Analytics with Hadoop

This course offers an in-depth hands-on exploration of various cutting-edge information technologies used for big data analytics. The first half of the course will focus on using big data management techniques for ETL (extract-transform-load) operations. The second half of the course will focus on using big data analytics tools for data mining algorithms including classification, clustering, and collaborative filtering. The course is extremely hands-on, and will require you to spend significant time working with large datasets. Students are expected to have taken at least one course in data modeling and one course in data mining (please see pre-requisites) or have significant related work experience. During the course, students should expect to become familiar with the Unix operating system, as well as with programming in Python. During the course you may be required to install some software on your computers on your own, with very little support, if any, from the instructor or anyone else. You should be willing to trouble-shoot any issues during installation, drawing help from Google searches.

Prerequisites:

Prerequisite OPIM 5604 and 5272

Minimum Credits: 3.00

Maximum Credits: 3.00

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