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Six Sigma Green Belt (DMAIC Framework)

Lead full DMAIC projects with statistical rigour

5 hours 7 modules

The framework

DMAIC + Hypothesis Testing + Regression + DOE

Green Belt adds statistical depth to DMAIC: process capability indices (Cp, Cpk) for Measure; t-tests, ANOVA, and Chi-Square for Analyse; regression to find the vital few Xs; and basic DOE for Improve. Control adds SPC and Poka-Yoke.

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How you'll learn

Text-first. Practice-heavy. No video lectures.

15-minute text lessons

Short, dense reading you can finish between meetings — not hour-long video lectures.

Hands-on exercises

Apply the framework to a realistic scenario, right in the module where you learned it.

Quizzes & assessments

Check your judgment, not just your memory — most questions are situational.

Certificate on completion

Finish a course and get a shareable certificate, automatically.

About this course

Green Belts lead full DMAIC projects with statistical rigour. This course covers hypothesis testing, regression analysis, process capability, and Design of Experiments — all applied to realistic business datasets using Python.

The project: Full DMAIC Project

Lead a complete DMAIC project on a provided dataset of hospital patient wait times. Conduct hypothesis testing to identify root causes, build a regression model to quantify the key drivers, and design a control plan.

  1. 1

    Advanced Define — VOC, CTQ Tree, Project Scoping

    Translate customer voice into measurable quality characteristics.

    30 min· Knowledge check· 📚 1 resource
    Free preview
  2. 2

    Advanced Measure — Process Capability

    Cp, Cpk, Gauge R&R, and measurement system analysis.

    35 min· Knowledge check· Coding exercise
  3. 3

    Hypothesis Testing

    t-test, ANOVA, Chi-Square — choosing and interpreting the right test.

    40 min· Knowledge check· Coding exercise
  4. 4

    Regression Analysis

    Find the vital few Xs that drive process output.

    35 min· Knowledge check· Coding exercise
  5. 5

    Design of Experiments (DOE) Basics

    Full factorial designs to optimise multiple factors simultaneously.

    30 min· Knowledge check· Coding exercise
  6. 6

    Advanced Control — SPC & Poka-Yoke

    Statistical process control and mistake-proofing.

    30 min· Knowledge check· Coding exercise
  7. 7

    Capstone: Full DMAIC Project

    Lead a complete DMAIC project on hospital wait time data.

    30 min· Knowledge check· Coding exercise