A summarized list of data science concepts

Darryl Buswell

As a fun exercise, our team of Datakick Collaborators spent time discussing and collating a list of data science concepts.

As a fun exercise this morning, a bunch of our Datakick Collaborators spent time discussing and collating a list of all the data science concepts and techniques we have used. We thought it would be possible to summarize everything on a single page... We should have known better.

Either way, we believe the list can act as a fantastic resource for aspiring data scientists and data professionals. Think of it as a data science concept checklist. And while you most likely won't need to know every concept in detail, we believe all data scientists should have some basic awareness of everything we have listed out.

It appears you don't have a PDF plugin for this browser. No biggie... you can click here to download the PDF.

What's next? Well, our next round will see us focus more on the tools and technologies which data scientists tend to use. Particularly those which are open sourced. And we are seriously under-representing many of the concepts and techniques on the data engineering side here too. So, who knows, we may look to create a second list for those concepts.

Want to help us out? Come join our growing group of Datakick Collaborators.




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