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Learner Reviews & Feedback for Data Analytics for Lean Six Sigma by University of Amsterdam

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3,477 ratings

About the Course

Welcome to this course on Data Analytics for Lean Six Sigma. In this course you will learn data analytics techniques that are typically useful within Lean Six Sigma improvement projects. At the end of this course you are able to analyse and interpret data gathered within such a project. You will be able to use Minitab to analyse the data. I will also briefly explain what Lean Six Sigma is. I will emphasize on use of data analytics tools and the interpretation of the outcome. I will use many different examples from actual Lean Six Sigma projects to illustrate all tools. I will not discuss any mathematical background. The setting we chose for our data example is a Lean Six Sigma improvement project. However data analytics tools are very widely applicable. So you will find that you will learn techniques that you can use in a broader setting apart from improvement projects. I hope that you enjoy this course and good luck! Dr. Inez Zwetsloot & the IBIS UvA team...

Top reviews

LH

Jun 28, 2022

I couldn't stop, I enjoyed this class so much I completed it early!!!! I love how it was interactive and the exercises were very helpful. Thank you. Instructor was very knowledgeable, too.

JL

Apr 28, 2020

I really love this course as I've learned a lot from it. All the techniques and learning I've acquired here would definitely help me a lot in my current role and projects. Thank you Dr. Inez!

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By Eduardo A

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Nov 11, 2017

Excellent

By Ahmed H

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Nov 9, 2017

very good

By Magali O

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Dec 17, 2020

excelent

By LA B

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Aug 22, 2022

awesome

By Randall D

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Jan 6, 2020

love it

By Andrea S C

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Oct 28, 2019

PERFECT

By Daniela C S d Z R

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May 26, 2017

So good

By Kalilou i S

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Feb 17, 2023

Good !

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Apr 26, 2022

goood.

By Na R

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Apr 30, 2019

Rate 5

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Feb 6, 2019

Thanks

By Dr. A I A D ( O - G A D

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Oct 16, 2025

great

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Feb 1, 2025

bien.

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Oct 15, 2024

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Jul 7, 2021

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Dec 25, 2019

great

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Aug 3, 2019

Great

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Oct 28, 2025

卮賰乇丕

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Jul 9, 2025

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Oct 10, 2023

good

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May 10, 2022

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Aug 10, 2021

nice

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Sep 22, 2020

good

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Jul 11, 2020

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