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In contrast to 2015, when the Data Science hype was rolling across Germany, we now do have more and more universities offering specializations or whole degrees in Data Science and tightly related disciplines. Yet, still many aspiring Data Scientists have completed different studies, e.g., computer science, physics, mathematics or economics. To be honest - I highly appreciate the diverse backgrounds of Data Scientists I have been collaborating with.

Coming from a non-DS field, you'll need to do some additional homework in order to keep up with ML natives. But in the age of MOOCs (massive open online courses), there are enough offerings. I'll try to provide an overview and give some guidance. 

This guide does not claim to be complete in any way, but hopes to be informative. If you feel like a relevant course is missing, feel free to contact me.

Introductory talks

If you need some overview about what AI and Data Science are and what they can be used for, you can start in this section. The duration is below 1h, so you should get lots of insights in a minimal amount of time. Especially as a business person trying to understand some aspects and implications, these might be a good choice.

Yufeng Guo (Google AI Adventures) - What is Machine Learning?

In some brief videos Yufeng gives a nice introduction into Machine Learning, explaining basic concepts and the process of ML. 

What is Machine Learning?

The seven steps of Machine Learning

Kevin Kelly - How AI can bring on a second industrial revolution

"Only by embracing AI we can steer it". Kevin Kelly talks about cognification and the many facets of intelligence. He then describes how AI will drive a second industrial revolution.

Very inspirational talk that helps understanding the big picture.

Nick Bostrom - What happens when our computers get smarter than we are?

Swedish philosopher Nick Bostrom turned famous by writing his book "Superintelligence: Paths, dangers, strategies". Here, he shares ome of his thoughts around the hypothetical problems coming up with the rise of superintelligent systems. He explaings the risks associated to it and elaborates ways to mitigate the risks from the beginning.

A must-view if you are interested in AI and Machine Learning. 

Kenneth Cukier - Big data is better data

Old, but gold - in 2014, Kenneth Cukier, Data Editor at The Economist, gives a quick insight how Big Data and Machine Learning are going to change our lives and the big responsibilites that come with Big Data.

Still very true, and definitely worth watching.

Grady Booch - Don't fear superintelligent AI

IBM's Grady Booch gives a nice statement regarding superintelligent AI. He opposes to great minds like Nick Bostrom, Stephen Hawking and Elon Musk. His way of presenting is very entertaining, but his thoughts are deep. He includes allusions to many movies like 2001, The Terminator and Matrix.

Even though I do not agree to everything, it provides nice impulses to start thinking.