Data Analytics

ITWS-4600

The world at-large is confronted with increasingly larger and complex sets of structured/unstructured information; from cyber and human sources. Traditional enterprises are moving toward analytics-driven approaches for core business functions. Data and information analytics extends analysis (descriptive models of data) by using data mining and machine learning methods, with optimization and validation, to recommend action or guide and communicate decision-making. Thus, analytics is an entire methodology rather than individual analyses or analysis steps.

3 credits
Prereqs:
none

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2023
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 2/10
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 2/7
2022
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 8/10
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 4/7
2021
Data Analytics (3c)
  • Thilanka Munasinghe
  • Linda Kramarchyk
Seats Taken: 7/10
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 3/5
2020
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 10/60
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 3/5
2019
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 4/60
Data Analytics (3c)
  • Thilanka Munasinghe
Seats Taken: 7/10
2018
Data Analytics (3c)
  • Linda Kramarchyk
  • Peter A Fox
Seats Taken: 11/13
Data Analytics (3c)
  • Peter A Fox
Seats Taken: 1/15
2017
Data Analytics (3c)
  • Gregory N. Hughes
  • Melissa Natalie Hay
  • Peter A Fox
Seats Taken: 8/25
2016
Datal Analytics (3c)
  • Peter A Fox
Seats Taken: 3/25
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998