With respect to everyone around the world who is suffering right now, and at the risk of tone-deaf blogging, I have to share that I feel like a million bucks today, because last night I passed the final project in the Microsoft Professional Program in Data Science. It's been a nine-month journey through nine courses plus that capstone project, and it's made a huge impact on how I approach data projects, from small "hobby" data analysis to multi-year enterprise data initiatives. It's also made a huge difference in my confidence level generally.
When Microsoft launched the program internally back in April 2016, with the ambitious goal of addressing the US technology gap in computer sciences while bringing more diversity into the available pool of candidates, I was fortunate to get into the pilot program. This meant that the low cost of each course (about $50 per course at the time I went through them) was covered by Microsoft, and I had my manager's and team's support for the time commitment. Several of my team-mates joined the pilot at the same time, and we were also able to nominate the technical and data-focused folks at our partners to go through it with us.
The public launch happened July 2016. You can find the full description of the program here and the course schedule here. The track diverges at several points, allowing you to choose, for example, whether to learn R or Python (although you could certainly take all the courses). I highly recommend it for anyone who loves data and wants to learn more about how to wrangle it. Here's why:
What I loved about the program:
- excellent, engaging teachers and well-thought-out content.
- active discussion forums and community support, quick responses from the program coordinators.
- getting hands-on in a way I certainly wouldn't have if I'd only explored these concepts on my own through tutorials and demo videos.
- the flexibility to learn at my own pace, and to choose where to dig in and where to skim.
- being part of a diverse cohort of data lovers from around the world
What I learned:
- an appreciation for the complexity of data science. These courses provide a great foundation, but they also make it clear that non-technical factors like experience, dedication to the truth, resistance to easy answers and correlations, creativity in problem-solving, and patience and perseverance are what separate a good data scientist from a great one.
- how to use the tools. Microsoft makes software like Power BI and Azure Machine Learning Studio that is so easy to use, you might feel like you can pick them up in a few minutes. The hands-on labs in this course showed the real power in these programs, and how the pieces of the stack fit together.
- about myself: I learned that it's possible to take on a degree program with an already-full life, and that it's actually fun to learn intimidating new skills. For example, the final project, which I vaguely dreaded through the nine preceding courses, turned out to be an addictive daily pursuit that felt more like a puzzle than a science project.
What you should know if you're considering this program:
- If you already have a database or developer background, that will help with some of the courses, but you probably won't sail through them all!
- if you do NOT have lots of database or programming experience, you can still do this! But the courses will probably take you more like 20 hours each than 8 hours.
- you can audit the courses for free, but if you want the certificate, you need to purchase the "verified certificate" for each course (and pass them)
- If Data Science isn't your thing, more MPPs are coming - expect future tracks to open in 2017 including topics like Big Data Engineering and Front End Web Development.
Who helped me:
I hit snags and lost my nerve many times along the way. I wouldn't have made it through without a village. So let me take this opportunity to very publicly thank the folks who talked me down, pumped me up, let me phone-a-friend, and otherwise were There For Me:
& all the folks on the Yammer and edX discussion threads who asked the questions I wanted to ask, raised issues and got them resolved before I encountered them, and provided suggestions and encouragement.
Finally, thank you Graeme Malcolm & the entire team (I'm guessing more of an army than a village in this case) who made this program possible.
I am employed by Microsoft, and the opinions expressed herein are my own.