I wanted to take this fantastic course at Coursera, but I did not have access to Minitab. The solution? Perform all analysis and exercises with Python instead.

It's been a long time since I was not that happy with a course until I found the University of Amsterdam's Data Analytics for Lean Six Sigma at Coursera. This course has really been helpful in understanding Data Analytics and finding the right solutions for plenty of industrial situations. The instructor Dr. Inez Zwetsloot did a great job by clearly explaining all the content in a structured manner. I cannot explain how thankful I am for all the acquired knowledge. However, I did not have access to the Software Minitab so I took it without the hands-on experience... This was not a good idea. Hence, I wondered if I could have an alternative to Minitab to put into practice along with the course, and I found it with Python.

This repository has all the Python coding to perform the examples and exercises Dr. Zwetsloot does in Minitab but with packages such as Numpy, Pandas, Matplotlib, Seaborn, Scipy, Reliability, and Statsmodels. This just pretends to be an alternative, acknowledging that Minitab is a very powerful tool for statistical analysis. This has been challenging to find a straightforward way to perform the same analysis by coding in Python, but that also strengthened the learning.

The data to do all examples and exercises can be downloaded from the course itself. I Hope this freeware alternative could be helpful for someone interested in learning Data Analytics.

See it on GitHub: https://github.com/ArnaldoMatute/Coursera-Data-Analytics-for-Lean-Six-Sigma