Last week I finished a 12-week Web Development Immersive at General Assembly, and next week I am starting a new free and open-source journey by joining in on the “Summer of Data Science” — a commitment to learning something new about data science and sharing it publicly.
Rewind. How did I get here? When I made the decision to quit my full-time job in civic tech, my rationale went a bit like this:
“I’ve spent so much time at the intersection of technology and social justice, but on the business side of things. I may not come out on the other end of this ‘boot camp’ as the next greatest web developer, but I know it can’t hurt to be more technical than I am today.”
Tech fluency is an ever-growing important skillset for all careers. Not because we are all required to build tech or manage it, but because technology strengthens the solutions to the world’s toughest problems, at scale.
As I went through my 80-hour weeks of coding, training new thought patterns (No, Meag, you are no longer the project manager, but the engineer), and hitting more brick walls and moments of vulnerability than ever before, I continued to be distracted by the idea that, software is a means to end.
Looking back at my earlier career in digital health, I was reminded of the mission we had at the Center for Connected Health, ‘Enabling improved patient outcomes through technology.’ Simple, yet powerful. This mission has been a guiding operating principle in my career and framed my thought process for the four web development projects I built over the past three months: a data visualization for Congressional spending, a data-driven landing page for Consumer Financial Protection Bureau complaints, an easy-to-use talking points application for the busy elected official, and a flashcard game for newly minted international development professionals.
While these projects grew in complexity over time, from using HTML/CSS and jQuery to React and d3 — my mission was the same: build something people can use. Okay — what makes something ‘people can use’? A lot of things, but from my experience, these applications are the scaffolding for the information we seed it with.
Enter data science.
None of the aforementioned projects are any good without robust sources of data. While I’ve dedicated the past quarter on web development studies, I am thrilled and excited about the opportunity of taking a mess of data and turning into something we can all see and understand.
Creating order from chaos.
So — how do I get there? Well, in the process of teaching myself Python and d3, thanks to the help of many smart people, most notably —
, for his incredibly accessible blog and entertaining podcast — I stumbled upon ‘Summer of Data Science.’
At first it sounded like something I should have done in the summer before high school, but upon further research I fell in love with the idea of joining a vibrant community led by Renee Teate (@BecomingDataSci) to explore what the hell goes on with data mining, wrangling, munging, analyzing, visualizing, etc.
Without being too overwhelmed by the available resources for beginners, I am going back to basics with statistics, linear algebra, and the rest of math I’ve forgotten.
Here’s how I am planning my Summer of Data Science:
- Attend 1–2 meet-ups per week. D.C. is great for this!
- 10–15 hours of dedicated course work based off the curriculum over at Open Source Data Masters.
- My initial goals, albeit not very SMART ones, are to gain proficiency in SQL, Python, and Javascript (more focused on web dev)
And why this trending hashtag, and not a Coursera course or some other freemium option?
- Public accountability is good for me.
- Joining a large community accelerates learning from varied perspectives.
- And tangentially, the best time to plant a tree was 20 years ago. The second best time is now.
You don’t need a PhD to be interested and explore something new. Follow along on Twitter @SoDS17, or even better — join me!
