Data mining is the computationally intelligent extraction of information from large databases. It is the process of automated presentation of patterns, rules, and functions from large data bases to make crucial business decisions. This course takes a multi-disciplinary approach to data mining and knowledge discovery involving statistics, rule and tree induction, neural networks, genetic algorithms, visualization and fuzzy logic. The course is project driven and puts a special emphasis on the use of computational intelligence for scientific data mining related to drug design and bioinformatics.
Spring | Summer | Fall | ||
---|---|---|---|---|
(Session 1) | (Session 2) | |||
2023 | ||||
2022 | ||||
2021 | ||||
2020 |
Knowledge Discovery With Data Mining (3c)
|
|||
2019 |
Knowledge Discovery With Data Mining (3c)
|
|||
2018 |
Knowledge Discovery With Data Mining (3c)
|
|||
2017 | ||||
2016 | ||||
2015 |
Knowledge Discovery With Data Mining (3c)
|
|||
2014 |
Knowledge Discovery With Data Mining (3c)
|
|||
2013 |
Knowldge Discovry W/datamining (3c)
|
|||
2012 |
Knowldge Discovry W/datamining (3c)
|
|||
2011 | ||||
2010 | ||||
2009 | ||||
2008 | ||||
2007 | ||||
2006 | ||||
2005 | ||||
2004 | ||||
2003 | ||||
2002 | ||||
2001 | ||||
2000 | ||||
1999 | ||||
1998 |