Data Science Education

  • Comments posted to this topic are about the item Data Science Education

  • I very much agree with this. As an individual there is a lot we can do for ourselves. Where it gets interesting is where the there is a management approach[/url] set up to support staff learning

  • I dislike the trend for very specific degrees. You get too many people selecting degrees in games programming, for example, when there isn't the jobs to support the numbers of the annual influx of new initiates.

    What I would like to see is value put on modules, such as data analysis, which would be interesting enough to be selected by many, add value to many peoples' career and ensure a better groundswell of understanding.

    Gaz

    -- Stop your grinnin' and drop your linen...they're everywhere!!!

  • ...contributed to the general distrust of certifications today...

    I have interviewed far too many that have attained certifications but garnered little or no understanding. I got to the point that when friends and colleagues were thinking of going for the certifications that I asked them what they hoped to get out of it and how.

    Gaz

    -- Stop your grinnin' and drop your linen...they're everywhere!!!

  • I must admit I think that course looks really helpful, I've enrolled and will go through it.

    Anyone been there and done it yet?

  • Udemy is also a good resource. You get professionals who work in related fields trying to make extra cash who teach real-world examples there in various degrees of levels.

    I work on a team of data scientist, me being the technical resource to fill the void and support those guys. We have quite a few who are getting or have received their masters in statistics. Most would agree that if you want to pursue data science, statistics and related are absolutely critical to working on the level of projects needed utilizing tools like R, SAS, STAT or Python.

    What I've found to be a huge need for the organizations in my area are the data scientist who not only know statistics and probability, but also know databases, ETL and modeling. Those who can not only crunch data in R, SAS and Python, but can also be self-service with the data platforms available. Once you have that, the real topper is knowing how to both act on the insights you unearth and being able to communicate it effectively to the end user.

  • I hated statistics in college (though my degree was in Math) and now I find myself a "data scientist." How ironic.

  • I agree with the premise. Education is a good thing. However, we need to consider that "everyone has a bias", and that seems to be especially true with a lot of these online courses. Khan Academy is a great example as my kid's schools use that. Frequently it presents historical information incorrectly in an attempt to push a particular agenda. Statistics is an area where you can "teach the facts" or easily introduce bias. We see that today in politics, the media doesn't like the results of a poll so they change the methodology. We can debate that all day long, but the point is - don't just accept that what is being offered as truth is really true. Review multiple sources, consider ideas critically, use your head.

    I have worked with people in the past who "knew" something was true because their instructor told them so. Frequently it could be proven false in a matter of minutes. I fondly recall my enjoyment in one particular case, watching their faces as they realized their prized professor was a liar when he claimed that Java is faster than C++.

    Use your head. If something is presented that you can reproduce on your own, great. When ideas get presented as fact, but there isn't solid unbiased evidence, question it. You will be a better person for it, whether your investigation finds it correct or incorrect.

    Dave

  • xsevensinzx (9/15/2016)


    Udemy is also a good resource. You get professionals who work in related fields trying to make extra cash who teach real-world examples there in various degrees of levels.

    Be a little careful with Udemy. Many of their courses are fine, but they keep 'selling' plagiarised courses (from Pluralsight or elsewhere). Worth doing homework on the course before paying.

    I like Coursera, Academic courses more than technical, lots of courses offered by universities and in many cases are free if you don't want the certificate. I've just finished a Machine Learning course there and I'm starting a Statistics course.

    Gail Shaw
    Microsoft Certified Master: SQL Server, MVP, M.Sc (Comp Sci)
    SQL In The Wild: Discussions on DB performance with occasional diversions into recoverability

    We walk in the dark places no others will enter
    We stand on the bridge and no one may pass
  • Analyzing data while in the process of performing your job as a DBA is not really "science". It's just like knowing a little something about chemistry can help you be a better cook, but what you do in your kitchen is totally different from what the FDA or DuPont is doing in their lab.

    "Do not seek to follow in the footsteps of the wise. Instead, seek what they sought." - Matsuo Basho

  • Analyzing data while in the process of performing your job as a DBA is not really "science".

    I'd agree with that.

    I worked as a programmer for a data science department at GE (much like a previous poster, I filled a technical gap) and the stuff the data scientists were doing went waaaaay beyond aggregating and doing the occasional regression. They were into all sorts of AI techniques, machine learning and so forth and every single one of them had a directly relevant PHD - these were not people who'd drifted into it.

    I suspect they were at the sharp end of data science (I have no other experience to compare them to but that was my impression) so maybe there some slightly less involved roles to get into but I'd say that anyone who was hoping to self educate their way into a Data Science career should prepare themselves for a STEEP learning curve.

  • GilaMonster (9/15/2016)


    xsevensinzx (9/15/2016)


    Udemy is also a good resource. You get professionals who work in related fields trying to make extra cash who teach real-world examples there in various degrees of levels.

    Be a little careful with Udemy. Many of their courses are fine, but they keep 'selling' plagiarised courses (from Pluralsight or elsewhere). Worth doing homework on the course before paying.

    I like Coursera, Academic courses more than technical, lots of courses offered by universities and in many cases are free if you don't want the certificate. I've just finished a Machine Learning course there and I'm starting a Statistics course.

    Good point, and I should have thought to mention that. For those of us with an IOS device, iTunes U has a lot, and I have found the Stanford courses to be well done, usually taught by professors who are more interested in teaching than in indoctrination.

    Dave

  • I don't see data science as something you get a degree or certification in, it's a practical skill acquired through practice not through studying theory. And to actual be effective at it also requires being at least somewhat well versed in whatever subject matter you're trying to analyze. There are certainly degrees very relevant to it however.

  • ZZartin (9/15/2016)


    I don't see data science as something you get a degree or certification in, it's a practical skill acquired through practice not through studying theory. And to actual be effective at it also requires being at least somewhat well versed in whatever subject matter you're trying to analyze. There are certainly degrees very relevant to it however.

    Domain experience certainly goes a long way with data scientist, but there is theory here much like there is in computer science because these guys are both using and developing complex algorithms, doing machine learning, deep learning and other advanced computational methods. If you're thinking these guys are just using Excel or running simple linear regression models, then you're really only scratching the surface.

  • Data Science belongs more on the Business Intelligence wing of the IT department, rather than over in the DBA wing. Certainly we as a DBA can leverage tools like Excel PowerPivot or Analysis Services in their everyday job, so we're not attacking every problem with a SQL hammer. We also need to familiarize ourselves with with princiapals of technologies like Hadoop or Tableau, because as Data Science becomes more ubiquitous we'll no doubt end up managing the environment and providing tier one support.

    "Do not seek to follow in the footsteps of the wise. Instead, seek what they sought." - Matsuo Basho

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