Overview

A regional healthcare system looked to RIT for a customized Lean Six Sigma training program with content tailored to employee needs and a format that could accommodate a distributed organization.  RIT worked with the client to adjust program content and then packaged it as a combination of three 2-day sessions delivered onsite plus four self-paced online modules and three live day-long project review sessions via web-conferencing.  The program has been repeated several times in response to changing employee skillsets and demographics.

The advanced R&D group of a major international manufacturing organization recently turned to RIT's CQAS for assistance in developing a short course as an introduction to data mining.  Due to the success of this initial course, additional courses were developed in advanced data mining techniques. The client wanted to provide advanced analytics education to their Lean Six Sigma Black Belt population as well as their scientists and engineers.  The course developed by RIT provided participants with exposure to the most commonly used techniques of modern data mining. All concepts and techniques were introduced via real life case studies, most of which used benchmark data sets that have been used over many years to test the strengths and weaknesses of new data mining methods.

When a pharmaceutical manufacturer wanted to upgrade the skills of their quality assurance group, they turned to RIT's CQAS to develop a customized training program in Statistics Fundamentals for Process and Quality Control. The objectives of the course developed by RIT were to make participants aware of the need for sound statistical principles in their work, and to provide them with fundamental tools to help make better data driven decisions.  By the end of course, participants were able to see the value of sound statistical methods, to distinguish a poorly designed study from a well-designed study, and to use these methods to analyze study data.