Hi Jered, thanks for the detailed comments. You raise several important points.
To be fair, it’s much easier for a numbers geek with no coding background to grow into a data science/analyst role than a coding geek with no numbers background. Which is probably a decent amount of FCC’s audience.
This article was originally published on Class Central, where the audience is online learners of all backgrounds. This is mentioned/hidden at the bottom of the post.
Without an extensive portfolio and experience…
A good portfolio is absolutely important. That portfolio can be acquired without formal education from a college or university. Kaggle competitions and Udacity Nanodegree projects are two popular and effective routes.
…most companies require a quant M.S. to even be considered, with a preference for Phd’s.
Yes, some companies will be off limits at this point in time. Where are you getting “most…to even be considered” from, though? These search results are filled with responses from data analysts and data scientists that are much more optimistic. We might even expect the shift away from Masters/PhDs to continue for two reasons:
- As William Chen mentions here (Do I need a Masters/PhD to become a data scientist?), we should expect more undergrads to enter data science in the future. “As more resources and relevant courses / programs become available to undergrads in the next 5–10 years, a lot more entry-level data scientists will come straight out of a Bachelor’s program. Then, you’ll start hearing a lot more about data scientists who started right after they finished their undergrad degree.” This indirectly applies to the online learner — the door for non-graduate students to enter industry will open wider.
- Online education works, the word is spreading, and more options are becoming available. Udacity, Coursera, edX, DataCamp, etc. are effective educators if you use them the right way. Industry has reacted and will continue to react to accept dedicated autodidacts as qualified candidates.