Please consider this course as an option and let Dr. Wierschem, CIS Department Chair, know if you have any questions.
Course Description: This course will introduce various techniques available to extract useful information from the large volumes of data an organization might possess. At the end of the semester, students would have been exposed to various techniques that will allow them to extract information from massive datasets. The course will cover concepts of large data analysis using techniques such as: association rules, decision trees, neural networks, classification and clustering. The focus is on how the techniques are to be used, and the details of the methods will be covered only to the extent necessary to understand when and how each technique can be used. Students will also gain experience using data mining software.
This course is recommended for CIS, Management, and
Marketing students.
This particular version of the course will include:
Neural networks and Bayesian Networks.
Only the QMST 2333 Business Statistics course is required
as a prerequisite. No prior programming
experience is assumed.
