Data Science Learning Journey – Months 4 and 5

A little behind on the updates here, so I’ll combine the last two months of this journey together. This will also likely be the last of these longer updates, as the journey has solidified its own long-term path. I’ll probably utilize LinkedIn going forward for mini updates.

The big update is this: next month I’ll start my first (official) classes as part of the Online Masters in Analytics (OMSA) through Georgia Tech.

I put official in parentheses above since I did take an audited class from this program this fall – Intro to Analytics Modeling – done through edX as a MOOC. I did homework, took tests, and was graded just as a student was, all of which I described in previous posts. I ended up getting a 90% in that class which I’m proud of and should mean that I can get “advanced standing” on that class (which is a required course for the masters). It gives me an extra slot to take an elective of my choice while doing the full program.

The class was a good introduction to the Masters at large (or at least from what I’ve read) and I enjoyed learning all about different types of models one can build from data sets (regressions, exponential smoothing, different categorization and classification models, etc..). The tests were tricky at times but manageable and made sure to gage understanding of using the correct model given a desired outcome or starting set of data.

As part of a course, I wrote a five page paper on bike sharing systems in large cities and what models could be used to make individual stations more effective (read: not run out of bikes or be full when someone wants to return one). I enjoyed putting some practicality behind the theoretical in the class and think of it terms of a popular program I see everyday (there’s a Citibike dock less than a block from my apartment).

It looks like, as part of the program, I’ll be starting a class in January called Computing for Data Analysis which is entirely in Python. My Analytics Modeling course was in R and I started this year’s learning adventure by self-teaching SQL, so this will be the third language to get exposed to.

I’ve really enjoyed learning from DataCamp before so I’m taking its Python Skill track (started just a few days ago) from the beginning, in hopes that I can grasp the language enough to understand the class (the timeline is about four weeks and I’m sure I’ll continue to learn after it starts).

What started as a journey of exploring a burgeoning interest of mine (moving past what I could do with an Excel file, for instance) has now become a commitment to a Masters of Science which will likely take two to three years to complete. So the journey will go on for some time and it’s really become something I’ve loved learning more about.

I don’t know where it will take my career but based on both data on the changing world of work and my own qualitative perspective, the analytics and data science skillsets are not going anywhere for a long time. It should provide some interesting and challenging work opportunities in the future.