Students frame questions and problems in forms that can be analyzed using data analytic tools. Students use data wrangling and preparation methods to prepare for analysis. Students use analytical tools to evaluate analytic models using linear/nonlinear multivariate methodologies. Students validate results and develop algorithms that can be used to make recommendations and forecasts. Students work with stakeholders to scope and frame questions and problems so that actionable results can be achieved.
Spring | Summer | Fall | ||
---|---|---|---|---|
(Session 1) | (Session 2) | |||
2023 |
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
|
2022 |
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
|
2021 |
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
|
2020 |
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
|
2019 |
Data-driven Decision Making (3c)
|
Data-driven Decision Making (3c)
|
||
2018 | ||||
2017 | ||||
2016 | ||||
2015 | ||||
2014 | ||||
2013 | ||||
2012 | ||||
2011 | ||||
2010 | ||||
2009 | ||||
2008 | ||||
2007 | ||||
2006 | ||||
2005 | ||||
2004 | ||||
2003 | ||||
2002 | ||||
2001 | ||||
2000 | ||||
1999 | ||||
1998 |