Graduate school test drive: Sample the first half of an evening graduate class
Monday, April 20
6 - 7:30 p.m.
SWENG 545: Data Mining
Data Mining studies automated ways of analyzing data in databases and data warehouses. Data warehouses are introduced including structure and design issues in their development. The main focus includes the theory and the methodology behind the tools used in data mining. These include techniques for data preprocessing, associative data mining and various techniques for classification and prediction type of problems. Preprocessing techniques such as variable reduction/selection, scaling of data and noise reduction are discussed. Variable reduction and/or selection include techniques such as principal component analysis, genetic algorithms and jack-knifing methods. Noise reduction includes gross error detection and correction and filtering methods. Associated data mining involves finding attributes in databases that tend to occur together. Once these are found, the question is whether they happened by chance or whether there is significance in their joint occurrence. Classification and Prediction include neural networks, linear discriminate analysis, multiple linear regression and subspace modeling methods such as partial least squares.
TONIGHT'S TEST DRIVE HAS BEEN CANCELED. Please contact Denita Wright Watson for more information about this Test Drive or future Test Drives at email@example.com or 610-648-3243.
Tuesday, April 21
6 - 7:30 p.m.
ENGMT 501: Engineering Management Science
Management science, alternatively known as operations research, is an interdisciplinary branch of mathematics that uses mathematical, analytical and statistical methods to improve decision making. In this class, these methods will be examined with respect to improving decisions in engineering and engineering management.
Contact Denita Wright Watson for more information: firstname.lastname@example.org or 610-648-3243.
Check back for future Test Drive dates.
Contact Ed Weckerly for more more information: email@example.com or 610-648-3248.