By Robert
Big house? Five cars? There’s no one universal way to do it, but get a coffee and read on through this bumper post to find your own way with the advice of real experts.
Last summer, Mrs G and I were in that ridiculously long line for the cablecar in San Francisco, like predictable British tourists, and got talking to the guys next to us. One of them, Jason Jackson, was just about to start studies in business including a good dose of quantitative research and data analysis. So, we’ve stayed in touch on Twitter. Recently, he asked me what the single best resource is for getting started in data science, and I found this a surprisingly tough question.
‘Data science’ is a term widely used in business and more computing-oriented circles, while it is not always recognised in slow-moving academia, where ‘statistics’ still holds sway. They are not the same thing. DS is a mix of skills to manipulate, analyse and interpret data, drawn from statistics, computer science and machine learning. It’s hard to be world-class at all of those, but there are probably a few really irritating people like that out there. To be autonomous and not get ripped off as a freelancer or entrepreneur, you should also know how to construct and work with databases and websites, and be able to make some data visualisations. It is probably sensible to devote little, if any, energy to Big Data. I mean, just watch a few YouTube videos about Spark and you’ll be OK.
If you want to study statistics, the route to take and resources to use are well mapped-out, but DS is not so clear. And remember that DS is only one step away from BS; there are plenty of websites promising a lot and providing little. Many of the …read more
Source:: r-bloggers.com