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Viewing: DNSC 6211 : Programming for Analytics

Last approved: Wed, 21 May 2014 08:35:30 GMT

Last edit: Mon, 19 May 2014 15:36:59 GMT

Catalog Pages referencing this course
School of Business
Decision Sciences (DNSC)
DNSC
6211
Programming for Analytics
Programming for Analytics
201403
3
Course Type
Lecture
Default Grading Method
Letter Grade

No
No

Corequisites

30
Kanungo
Frequency of Offering

Term(s) Offered

Are there Course Equivalents?
No
 
No
Fee Type


No


Accessing, preparation, handling, and processing data that differ in variety, volume, and velocity. The ability to handle and process data is a core capability in the context of any analytics position in the industry. Development of a theoretical grounding in emerging paradigms like schema-less data. The programming environments that will be typically employed include Python and R.

We are increasing the Computational Analytics course to 3 credits and emphasizing more programming.
Course Attribute

We are increasing the Computational Analytics course to 3 credits and emphasizing more programming.
cbeil (Mon, 19 May 2014 00:47:45 GMT): Rollback: I approved them by mistake.
Key: 1549