Six Sigma Yellow Belt Specialization

This specialization is for you if you are looking to learn more about Six Sigma or refresh your knowledge of the basic components of Six Sigma and Lean. Six Sigma skills are widely sought by employers both nationally and internationally. These skills have been proven to help improve business processes, performance, and quality assurance.

In this specialization, you will learn proven principles and tools specific to six sigma and lean.

This is a sequential, linear designed specialization that covers the introductory level content (at the "yellow belt" level) of Six Sigma and Lean. Yellow Belt knowledge is needed before advancing to Green Belt (which is a second specialization offered here on Coursera by the USG). Green Belt knowledge is needed before moving to a Black Belt.

The proper sequence of this specialization is:

  • Course #1 - Six Sigma Fundamentals
  • Course #2 - Six Sigma Tools for Define and Measure
  • Course #3 - Six Sigma Tools for Analyze
  • Course #4 - Six Sigma Tools for Improve and Control

At the end of Course #4 (Six Sigma Tools for Improve and Control), there is a peer-reviewed, capstone project. Successful completion of this project is necessary for full completion of this specialization.

It should be noted that completing either the Yellow Belt or Green Belt Specializations does not give the learner "professional accreditation" in Six Sigma. However, successful completion will assist in better preparation for such professional accreditation testing.

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    • Gregory Wiles, Ph.D., P.E.

      Interim Chair and Assistant Professor
       
      Department of Systems & Industrial Engineering
       
      • Bill Bailey

        Bill Bailey, Ph.D.

        Assistant Professor of Industrial Engineering
         
        Department of Systems and Industrial Engineering
         
      • David Cook, Ph.D.

        Assistant Professor of Mechanical Engineering Technology

        Department of Mechanical Engineering Technology

      • Christina Scherrer

        Christina R. Scherrer, Ph.D

        Professor of Industrial Engineering

        Department of Systems and Industrial Engineering

         



     

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