This is part four of a multi-part series. See the previous post here: https://careerchange.bearblog.dev/career-change-pt-3/

If you’ve been following my journey to a new career, then you know that my last post (linked above) was quite dire. I was, clearly, in a dark place when I wrote it. But even once I had a chance to clam down and reflect, the fact remained that I needed to make a change. What I was doing wasn’t working. My plan of learning to code, data analysis, and data visualization by only doing project after project was getting me nowhere fast. I looked at what I had accomplished over the past few months and all I saw was a trail of incomplete, failed projects. I know there are some people out there who can have an idea for a project and, without any experience, can build it piece by piece. To me, this always felt like someone with no carpentry or construction skills building a house from scratch. The truth is, for me, that’s exactly what it would be like. I have no coding experience to rely on. But, after reading dozens and dozens of posts about how to learn data analysis, science, and visualization, I see people, apparently, doing this all the time. What I finally realized, though, was that my situation is not the same. I recently read one blog where the author described how he went from “zero to data scientist” in 6 months, but in the first paragraph he talks about how he is a mechanical engineer! As if there is no coding or math involved in mechanical engineering! That is not starting from scratch. I am. And if I’m starting from a different place, then I’m going to need a different approach. So that’s what I’ve been doing for the past month.

Before you can lay the foundation of a house, you at least have to know how to use the tools. In this case, I choose Python. There are so many languages, just pick one you’re likely to use and learn it. Once you’ve learned one, it makes learning all the others that much easier (I hope). To do so, I’ve been utilizing lots of different resources from DataQuest to CodingBat to Brilliant to Codecademy. Some have been good. Others, not so good. In any course you take, there are going to be moments where you’re struggling to solve whatever problem you’re working on. The biggest challenge I’ve had in these moments isn’t how to solve the problem; rather if I should power through at all or if that would be a waste of my time. After all, there are no good roadmaps (that I’ve seen) for how to truly go from no coding experience to data journalist. Am I wasting my time by struggling through this for, potentially, days, or will I learn something valuable that helps me reach my goals?

I’ve done three things to try and solve this. First, I am laser confused on learning outcomes. Before I start any course I write down exactly what I want to be able to do. For example, “by the end of the course, I should be able to scrape a webpage full of links, find the physical addresses on the subsequent pages, and plot them on a map.” Then, I try to tie my learning outcome to a real world project I’ve got in my back project. In this case, I want to try and map out polling locations, which ties nicely to that learning outcome.

Second, , I’m keeping meticulous notes on what I’ve tried, what’s worked, what hasn’t. I plan on releasing all my notes as a sort of open source curriculum in the future to help others, but it also helps me now, by letting me spot patterns. For instance, when I’ve tried to follow along with YouTube tutorials, I find that the material doesn’t really sync in. (And I mean really follow along by coding alongside the video, not just watching it passively.) If I find a course that consists mostly of video tutorials, as opposed to active projects, I skip it.

That again speaks to the importance of projects. The third thing I do is keep projects in my back pocket. Even though I’m mostly focused on foundational learning, I haven’t abandoned projects all together. I try to spend a day a week applying what I’ve learned to a project (see: polling places) and that has seemed to help keep me on track.

Projects are still the best way to learn, but only if you’re ready for them. I’m in a unique situation and have needed to forge my own path. I’m sure that I’ll continue tweaking and making changes to my curriculum and plans as I go along, but I’m on a good path right now.