Six Sigma & Statistics Training
Self-paced courses with instructor support
Whether you want to learn just a few tools to get started, do a deep dive into statistical methods, or earn a Green Belt certificate, we've got you covered.
Customize your own training: Choose the Six Sigma tools you want to learn with our mini-courses.
Master the math: Our statistical mini-courses will guide you through hypothesis testing, regression, SPC and DoE so you really get it.
Earn a credential: Our Green Belt course teaches you the tools to lead Six Sigma projects from start to finish.
Click for details on the course design and lcomponents
Listen as Mary McShane Vaughn, University Training Partner's founder, discusses the value of online training. "Got an hour? Learn a tool."
Does technical online training really work?
How much do I need to learn to get started improving my processes?
You might have heard that Six Sigma Green or Black Belt training is really focused on statistics, and math is not your thing.
Here's a secret: most of the skills needed to improve processes involve no math at all!
That's right. By concentrating on choosing the right projects, taking stakeholders into account, leading a team, mapping processes and using common sense graphical and Lean approaches, you can start improving processes and making dramatic changes to the bottom line. No statistics required.
Stay tuned because we are working on a "Quick Start" bundle of courses that will give you the tools you need to get a jump start on quality improvement.
What if I'm looking for some formal training program, and not a mini-course?
We 've got that covered as well. We offer Yellow and Green Belt certificate courses for those who want a credential.
I'm already an experienced quality practitioner. What can University Training Partners offer me?
Even if you already have a Belt, there may be some topics that never really clicked for you.
How's your comfort level with fractional factorial designs, or Bayes' Theorem?
We are busy preparing mini-courses in probability, linear regression, design of experiments, and Quality 4.0 topics like classification and regression trees.