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As Big Data Plateaus, Data Science Education Grows

gthuang88 writes: Even as the hype around big data has died down, opportunities for data scientists are expanding. Johns Hopkins, NYU, and MIT are among the schools offering courses in data science, and IBM and other big companies are investing heavily in training programs. Now a startup called DataCamp has raised $1 million to expand online courses in R programming, Apache Spark, and other topics. The deal speaks to the opportunity that venture capitalists see in training the next generation of data scientists and business analysts. It also shows online education is specializing beyond platforms like Codecademy, Coursera, and Udacity.

3 of 41 comments (clear)

  1. R programming by tomhath · · Score: 2, Insightful

    There's no point in learning R if you don't have a solid background in statistics.

    1. Re:R programming by umafuckit · · Score: 3, Insightful

      I disagree. By learning R I developed a much better grounding in statistics than I had previously. This is because it doesn't hold your hand and you have to actually think in order to use it.

  2. Combo of CS, Stats, Analytics, & domain knowle by langelgjm · · Score: 4, Insightful

    While I think this has changed over time, initially I think some statisticians were suspicious of techniques coming out of computer science, e.g. SVMs. And still, machine learning is a rather niche field of statistics that requires a fluency in CS that many statisticians don't have (or need). Check out this discussion.

    Of course there are some statisticians who are also good CS people (think Trevor Hastie and Rob Tibshirani). And a lot of stats people have great domain knowledge in their areas. But I think "data science" is supposed to be the combination of stats, CS, practical programming ability (e.g., cleaning and manipulating large datasets, which is definitely not part of traditional CS or stats education), ability to communicate results effectively, maybe throw in some visualization, knowledge of how to query databases, and domain knowledge to interpret what data mean. Also, some types of data (e.g. text with the aim of NLP) are pretty infrequently touched upon in stats education.

    That said, I get the sense that a lot of places looking for "data scientists" are actually just looking for business intelligence people.

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