KDnuggets Top Posts for September 2022: Free Python for Data Science Course

We hope you all had a fantastic September, and are enjoying what October has brought them.

In regards to KDnuggets September top posts, we first and foremost want to thank all of our readers, without whom there would be no top posts to report any month. So, thank you!

Before we get to the top posts of the month, I want to let you know about an incentive we had for the most viewed original community submission for September. The book "Super Study Guide: Algorithms & Data Structures" was generously donated by its authors and friends of KDnuggets Afshine and Shervine Amidi. From the authors:

This book is a concise and illustrated guide for anyone who wants to brush up on their fundamentals in the context of coding interviews, computer science classes or to satisfy their own curiosity.

We sincerely appreciate this gesture, Afshine and Shervine, and are happy to pass this book along to the author of the community submitted original post which garnered the most views in the month of September, which was Combining Pandas DataFrames Made Simple, by Kanwal Mehreen. Kanwal wrote a fantastic overview on this topic, and I suggest anyone who has not yet done so to have a look at it.

And now on to the top posts of September.

1. Free Python for Data Science Course by Matthew Mayo
2. 7 Machine Learning Portfolio Projects to Boost the Resume by Abid Ali Awan
3. Free Algorithms in Python Course by Matthew Mayo
4. How to Select Rows and Columns in Pandas Using [ ], .loc, iloc, .at and .iat by Manu Jeevan
5. 5 Data Science Skills That Pay & 5 That Don't by Nisha Arya
6. Everything You’ve Ever Wanted to Know About Machine Learning by Cassie Kozyrkov
7. Free SQL and Database Course by Matthew Mayo
8. 7 Data Analytics Interview Questions & Answers by Abid Ali Awan

The most viewed post on KDnuggets for the month was Free Python for Data Science Course by Matthew Mayo, an overview of a course from freeCodeCamp for anyone looking to learn Python and its ecosystem for data science.

Additional posts included those demonstrating quality machine learning projects to help the portfolio; ways to select rows and columns in Pandas; data science skills worthy of your attention; a full overview of machine learning; a data analytics interview Q&A; and a few additional posts on free courses covering algorithms in Python and getting up to speed with SQL and databases. All are worthy of a read, and we hope you enjoyed all of these, and other, posts during September.

Thanks to all of our contributors, both in-house and community-wide. We hope you keep reading in October, and we'll see you here again next month.