Mike Allen's Blog

Doing Smarter Things With IT

Microsoft Professional Program for Data Science

I recently completed the new Microsoft Professional Program Certificate in Data Science. I've a background in software and data migration, and I knew how to use the tools. The course was intended to formalise my skills. Well, was I in for a surprise.

I'd already completed the Power BI Course, and first up was Querying Data with SQL, what could possibly go wrong? The courses were through edX and were mainly USD $50, they have all gone up to $100 since then.

The first speed bump was choosing a statistical language, I flipped a coin between R and Python a few times, and the gods of statistics seemed to favour R. There was also a new plug-in for R in Visual Studio, which made life easier. I kind of fell in love with R, anyone who likes to manipulate a whole dataset at a time would be at home with this language. My favourite bit of code just extracts the year from a date column and adds it as a new column on the end, cool! The density graphs are an absolute delight, as are all the graphical functions. There are R packages for everything and a vibrant user community, this is all good. I also found R useful for generating test data.

Next up was learning some real Statistical Thinking with ColumbiaX. I had done my stats training years ago while studying Applied Science. This course cleaned out all the cobwebs and got me enthused, there are more stats courses from ColumbiaX which I may get into in the future. Great stuff to get one Statistically Thinking. They've taken this off the Data Science track now, I can see why, but it needs a suitable replacement.

Then things got a little more technical with the Principles of Machine Learning. I'll never look at a regression graph in the same way. the introduction to Azure Machine Learning was a real epiphany of drag and drop Data Science. This is amazing stuff and right at the leading edge of cloud technology. I've has some exposure to Azure but this was really something else. Although calling an Azure Web Service from Excel did give me a touch of cognitive dissonance. Another great feature I found in Azure was Jupyter Notebook, which is a lovely open source intelligent notebook that can execute code. Wow! Executable notes!

I think every design team could benefit from this, what a way to prototype data transformations.

My decision to do the Developing Intelligent Application was a little off track, but I bought a book on C# to help me. This is part of the Applied Data Science section and there are some more data oriented courses available. Developing a bot was fun, and there was lot in this course. Analysing Twitter Feeds was great and bought in the Azure IoT hub and other Azure elements. This is obviously very popular and you can do all this with Microsoft Flow now :-(. Lot's more technical stuff in this one, I've even made friends with JSON. I did discover that SQL is useful for data analytics, the old is made new again!

The final Capstone project was a return to data analysis and Machine Learning. The hardest bit was writing the Data Analysis report and reviewing other students’ efforts.

This Certification took me over six months to complete and I learned a lot along the way. I paid for all the courses to get certification, however casual auditing of the course is available. The Professional Program offers a good conceptual learning alternative for those not seeking Microsoft technical certification. I suppose the down side is that you are expected to do a lot of technical things, like C#, and get no real certification for it.

I can't speak more highly of edX. Their courses are so well organised, the platform is easy to use and the content is excellent. Microsoft have made a great choice in partnering with them.

Was it all worth it? Absolutely! I'll be back to edX as soon as I've finished my book on Bayesian Analysis :-).

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