4 ms·
I'm biased as a non-technical analyst with an academic history, but I'm concerned that the curriculum doesn't meet the most basic needs. Quoting the section 'A
by blakerson 13y ago
I'm biased as a non-technical analyst with an academic history, but I'm concerned that the curriculum doesn't meet the most basic needs.
Quoting the section 'An Academic Shortfall':
"Academic credentials are important but not necessary for high-quality data science. The core aptitudes – curiosity, intellectual agility, statistical fluency, research stamina, scientific rigor, skeptical nature – that distinguish the best data scientists are widely distributed throughout the population."
In my estimation, none of those aptitudes are covered by teaching technical skills like databases, NLP, ML, graphical models, and the other topics this curriculum covers.
The "core aptitudes" generally boil down to asking the correct questions, establishing the correct answers, and correctly defending them. Academia doesn't automatically instill these skills, but it can do a great job of doing so.
Either way, inside or outside the ivory tower, an ace programmer who masters NLP, ML, Hadoop, and everything else could easily still come out without the required core aptitudes, and be thoroughly unprepared to do what data scientists are really expected to do: answer questions.
- craigching 13y agoIt's an open source curriculum, so you could get involved and help mold it to meet what you see are its needs as a curriculum, no? I'm not sure what I think of it yet as a curriculum, but I am bookmarking it and plan to come back to it for more resources. Personally, I think it's an interesting idea and something I want to watch to see how it unfolds.
- blakerson 13y agoI'm happy to share what I learned, but sadly, everything I learned was in a classroom lecture, and the course isn't available online. There may be something on one of the major MOOC hubs, though. I'll keep an eye out.
- SkyMarshal 13y agoThe best advice I've both heard and passed on, when asked about hiring "data scientists", is you want someone who can look at raw data, massage it, and develop their own original opinions and insights about it, preferably derived from a deep understanding of the nuances of statistics and probability and the messy real world. It's the judgement and insight you're primarily looking for. So, hire the best mathematician, statistician, probabilist, economist, or heck biologist, epidemiologist, etc. you can find, and then teach them the vocational tools - hadoop, etc.
- clarecorthell 13y agoSure, you can learn to use a technology and still be braindead or poor at analysis. This is an applied curriculum with a focus on specific technologies that enable an analysis-bent people to leverage their brains with technology. That's why data work is so beautiful -- it's space to demonstrate unquantifiables like curiosity, diligence, creativity, and grit. The quality of your projects is likely a good metric for your aptitude for data work, which is why I strongly advise working on a personal project. I'd love to get more pull requests with more materials that teach analysis!