On the Bertelsmann Technology Scholarship
This past November, I got accepted into the Bertelsmann Technology Scholarship offered by Udacity. You can learn more about the program and how it works here. I had applied to the Data Track program because of my interest in making sense of the unimaginable amounts of data that is being collected in a multitude of industries across the world today. How does one go about learning how to make sense of the data, in the right way?
I’d taken a couple of MOOCs in edX in the past — the quality of the courses there were top-notch, and I came out having learnt some R. I’d browsed through a bunch of tutorials in the Internet — some were pretty good and I’d be lying if I said I didn’t learn something there. By this point, I had some knowledge, yes, but also a desperate longing for a course that would teach me the solid fundamentals of Data Analysis.
I had viewed a few videos on YouTube to see if I could get a learning plan going. Heck, I’d even ordered a book to see if I could get something going. That ‘something’, it turns out, is momentum. Tightly tethered to momentum — I was about to discover — is a strong feeling of you belonging with like-minded people heading down the same road as you are, cheering each other on. There’s a sense of working together, helping each other out, motivating one another, and celebrating learning — every little nugget of knowledge that you can soak in — whatever it takes, to see each other beyond the finish line. And that, is the essence of what I’ve experienced after I was accepted to the Bertelsmann Technology Scholarship, signed up, and started with the program.
The lessons are excellent for a beginner in Data Analysis like me. You learn a concept and take interactive quizzes to solidify that concept even more. The difficulty builds up incrementally as you go along. If you are stuck and require help, there’s an entire community waiting to help you out and this aspect of the course is what makes taking it so exciting and fulfilling. The course starts you out with basic statistics, moves on to teaching you the fundamentals of the Python Programming language, and ends with guiding you on writing SQL queries.
The community is managed via Slack. There are separate channels by course lessons, topics, study-groups, Reddit-like AMAs, coding-practice (this is a popular one and has a Slack channel of its own), and so on. One channel that’s helped me build the momentum I talk about above is #60daysofudacity. You are encouraged to study (anything related to the subject matter) for at least 30 minutes every day and you post your progress to this channel. I have to say: I was skeptical at first. I mean, isn’t one of the core concepts of a MOOC something along the lines of you being able to ‘learn at your own pace’? With the kind of demanding schedule I must negotiate with every day, this would surely be impossible, right?
Not so right. I made a commitment and stuck to it. Turns out, studying for at least 30 minutes every day is no different from working out for 30 minutes everyday. It’s a habit you take the time and effort to build — for your own benefit; and in this case, for the benefit of others as well; see, you get to help out people who are perhaps stuck on the same problem as you did in the past but you have since figured it out and moved on along. After a few days, you want to study for 30 minutes at least once every day. And when you don’t — I took a break after Day 36 and wondered hiking up the Shivapuri hill in the Kathmandu valley which lesson I’d be on studying had I not taken a break that day — you find yourself thinking about it.
Whether or not I get into the 2nd phase (yes, there’s a 2nd phase of this course where you’re awarded with the coveted Nanodegree provided you complete the 2nd phase in its entirety), this habit of studying everyday that I now have built up — thanks to Udacity — will have been the biggest takeaway for me. Not to mention, some Data Analysis chops I think I’m in the process of acquiring.
This post has gotten longer than I intended it to be. Now, if you’ll excuse me, I have to go and import a bunch of CSVs into Postgres so that I can practice some ‘manic SQL queries’ (I’ve taken the liberty of borrowing this phrase from the SQL part of the course) locally on my machine. That’s my plan for today — Day 39, and it will take a lot longer than just 30 minutes.
Happy learning!
