Getting Started in Data Science Part 2

I’m finally getting around to writing Part 2 of Getting Started in Data Science. The first part can be found here. I made suggestions for university students interested in the field of Data Science. I even made a video about it too. 

Pick Two, Master One

Pick two computer languages and become proficient in one and a master at the other one. Or, pick a platform like H2O-Flow or RapidMiner and a language. Become a master at one but proficient in the other. This way you can set yourself apart from other students or applicants. 

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Startups and Open Source

This is my third startup. Or maybe my fourth, I’m not sure but it gets hazy after a while. What I do know is that if I ever do another startup, I’ll use open source to make it happen.

Let me explain with a bit of back history.

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Throwback to Gartner 2017

I was going through some old files when I stumbled across these old Gartner 2017 photos. What a great trip down memory lane with the RapidMiner team. We had so much fun down there.

Gartner 2017 image 1

Oh man, somewhere there’s a video of a colleague swimming in the fountain after a long night of drinking.

Gartner 2017 image 2

Plus there was so much intrigue. I was being wined and dined by a competitor that night too.

Gartner 2017 image 3

Times like these make for a life well lived.