Applied Analytics and Predictive Modeling

MGMT-6160

Business analytics enables organizations to leverage large volumes of data in order to make more informed decisions. It encompasses a range of approaches to integrating, organizing, and applying data in various settings. This course develops an understanding of concepts in business analytics and data manipulation. In particular, through hands-on experience with a range of techniques students will learn to work with large data sets, analyze trends and segments, and develop models for prediction and forecasting. This course is part of the Master's program in Business Analytics and builds on foundations learned in the fall semester.

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
App Analytics & Pred Modeling (3c)
  • Minor E. Gordon
Seats Taken: 36/50
2022
App Analytics & Pred Modeling (3c)
  • Lydia Manikonda
Seats Taken: 49/50
2021
App Analytics & Pred Modeling (3c)
  • Lydia Manikonda
Seats Taken: 47/50
2020
App Analytics & Pred Modeling (3c)
  • Lydia Manikonda
  • Yuan Xu
Seats Taken: 64/80
2019
App Analytics & Pred Modeling (3c)
  • Dorit Nevo
Seats Taken: 39/50
2018
Adv Analytics & Pred Modeling (3c)
  • Dorit Nevo
Seats Taken: 39/40
2017
Advanced Analytics (3c)
  • Dorit Nevo
Seats Taken: 24/30
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
New Ventures (3c)
  • Simon C. Balint
Seats Taken: 4/40
2004
2003
New Ventures (3c)
  • Nicholas M. Young
Seats Taken: 7/50
2002
New Ventures (3c)
  • William Stitt
Seats Taken: 27/50
2001
New Ventures (3c)
  • William Stitt
Seats Taken: 16/50
2000
New Ventures (3c)
  • William Stitt
Seats Taken: 25/45
1999
New Ventures (3c)
  • William Stitt
Seats Taken: 34/45
1998