Datasciencemasters.org Website Review

the open-source curriculum for learning data science. foundational in both theory and technologies, the osdsm breaks down the core with coursera, ebooks, stack overflow, and github -- all free and open -- how can you afford not to take advantage of an open source > ...by 2018 the united states will experience a shortage of 190,000 > skilled data scientists, and 1.5 million managers and an*lysts > there are little to no data scientists with 5 years experience, > because the job simply did not exist. -- david hardtke how to hire a data scientist 13 nov 2012 clas*ic academic conduits aren't providing data scientists -- this talent gap will be closed differently. > 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. >  > we’re likely to see more uncredentialed, inexperienced individuals > try their hands at data science, bootstrapping their skills on the > open-source ecosystem and using the diversity of modeling tools > available. just as data-science platforms and tools are > proliferating through the magic of open source, big data’s > data-scientist pool will as well. > and there’s yet another trend that will alleviate any talent gap: > the democratization of data science. while i agree wholeheartedly > with raden’s statement that “the crème-de-la-crème of data > scientists will fill roles in academia, technology vendors, wall > street, research and government,” i think he’s understating the > extent to which autodidacts – the self-taught, uncredentialed, > data-pas*ionate people – will come to play a significant role in > many organizations’ data science initiatives.