New Data Science Certificate Program

Personally, I'd prefer the less technology-specific topics already on offer. But, my employer would be much more likely to hire someone with UW's course-mix. So, there should be some demand for that.

And, if we are talking about a career decision, $3,000 is small potatoes compared to the value of getting the right topics.

The site appears to be push sponsor products and don't really talk about alternatives. Expect to see lots of endorsements of IBM products.

Of course, I wonder if this certificate gets me anywhere as far as employment goes.

Because this is the response of the "university system" trying to protect its cash flow. Perhaps you missed it, but udacity said recently it will do some certification program for "minimal costs", which was the beginning of the conversation. Education should be free (Khan style), says Udacity.

The University establishment's response is "here we will give you certificates, but you have to give us three grand."

Money for certificates, knowledge for free.

Ideally, no. We're witnessing an overuse of the name "data scientist" (which has its own problems, but that's another story). There's a non-trivial difference between a data scientist who understands the theory used for the EM algorithm or belief propagation, and a "data scientist" who is performing large-scale data analysis using various data mining tools.

Unfortunately, they're both getting lumped together. To become one of the former, you need graduate-level maths, CS, and statistics, while this certificate caters to the latter.

There's a lot of non-PhD level work that goes into a large research project, often for aspects you may not have considered like animal care.

A "Data Scientist" might be a specialized software developer, but it doesn't follow that they have only a superficial understanding of the inner workings, even if that understanding is not good enough on its own to do much original research.

This is the first I've heard the term "Data Scientist," though Harvard recently announced a masters-level "Computational Science and Engineering" degree. (http://news.harvard.edu/gazette/story/2012/06/a-new-masters-...)

The bottom line is that due to the amount of data being generated by research, demand for programmers to help deal with it is rising.

For example I couldn't implement an SVM library from scratch to save my life, but I do understand what it means to be a 'maximum margin' classifier, from a high level how the 'kernel trick' works, and why you would tune regularization and cost parameters. However this knowledge has been enough to help me in quite a few interesting problems.

Reading accounts of how others have solved real world data mining issues it's amazing how often a very simple model will do the job, and also how often, even among more serious researches, there's a bit of intuition in finding the right combination of parameters, and lots of trial and error in searching for which model/blend of models really does the job.

I think there's a lot of room for more people approaching data mining with the 'hacker' mentality. Sure you don't want 'data scientists' using a randomForest whose eyes glaze over when you mention the word "ensemble", or someone who couldn't explain in plain terms what a "maximum margin hyperplane" is. But, there is a growing space for practitioners in this space, that aren't necessarily as strong in the theory as people working in the pure research space.

Don't take my word for it, though--you should visit us and find out what data scientists do!

8 hours lecture online per week + whatever offline work, for 4 semesters. That format, at minimum passes the "sniff test". I think four semesters at that rate is long enough to legitimately teach the content.

My only question now is how well received is it by the world at large? Has anyone hands on experience with ITB?

My personal advice is to ignore any future advantages that may or may not come as a result and focus on doing it because you simply want to do it. If you enjoyed the process and feel fulfilled at the end, it doesn't matter what may come as a result. If you need to work hard to sell yourself on the idea of doing it, it is probably not worth doing.