Data Science and machine learning are very cool just now and It’s relatively easy to find lots of resources to learn either from books to MOOCs (massively Open Online Courses). But how can you prove you are an expert? The Microsoft tradition and one that I have followed in the past is to get certified and I often get to try the exams in beta form to help bed those in.
However when it comes to the world of Machine Learning for examle there are several technologies even from Microsoft:
- Azure Machine Learning with support for Python & R
- R Server
- CNTK (Cognitive Tool Kit)
Now imagine for a moment you wanted to be a good blogger – would a certification in WordPress, Word or the Open Live Writer this is written in be of help? Possibly, but only if you have grasped the principles of good blogging like understanding your audience (that’s a post for another day!). I would argue you need the theory and then get technically checked out on your tools of choice.
So I used spare time in the holiday season to mug up theory and techniques with the Microsoft Professional Program for Data Science rather than watch movie re-runs. The theory in this program comes from some excellent lecturers at American Universities such as Columbia , MIT, Duke etc). From what I have seen so far (4 passed one in progress) they are all high quality – both well constructed and well presented. It is also practical, and yes it is based on Microsoft technologies, but those technologies are there as in any course, to underpin the theory rather than being the subject being studied. A good example is the use of Azure Machine Learning in the DAT203x module (which also the best I have seen on this topic) where AML is simply used as a fast way to work through examples rather than writing unnecessary code – so not relevant to the learning objective.
The complete program requires completion of 10 modules (there are electives like options to do either R or Python) and each one of which will take a few weeks to get through especially if you want to learn this stuff and not just pass the course. The final module is a Data Science Challenge Project is there to prove to yourself and Microsoft that you really know what you are doing.
The knowledge check questions throughout the modules I have seen (except the final project), are in my opinion, just there to ensure you have done the exercises and not fast forwarded through all the videos. They will not, in my opinion, stress test your knowledge like a Microsoft certification. So yes you could skim through the professional program and possibly fudge your way through the final project or you could do what I do - reverse engineer some of the examples, read the recommended additional material and make copious notes like this ..
That you will get the intended value out of every module and properly ground you in the approach. After all if you don’t enjoy doing this stuff why would you study it?
This also means I will continue to do exams to compliment courses like this both to keep up with the new stuff1 and to keep the old brain ticking over especially as you can do them at home via a web cam (details are here).
1 by new stuff I don’t mean re-certifying which you can now do on the Microsoft Virtual Academy, I mean new exams on new technologies like Azure Machine Learning