I had every intention of writing this on Wednesday and then my statistics final got in the way, so thanks for being patient with me on that!

This post is meant as just a space for the things I didn’t get to go over in the rest of the series, but they don’t warrant their own post individually. Where I’m going to start with that is what to do when you get stuck on a piece of code or you have something you want to try but aren’t sure how to go about it.

Most types of search engines are likely to bring something up for you: Stack Overflow if you put in the exact error you’re getting. Google and Youtube for the same, and to see how to do something, to go step by step on a process that may be stumping you.

One of the first things I learned about programming in general was that it takes a lot of Googling the issues you run into or the things you want to do. You are not expected to know everything off the top of your head, and you have an entire world at your fingertips to figure out the problem.

I used a youtube video to figure out an ARIMA model for a technical assessment once, and it was how I figured out that the library/package being used was faulty.

I also want to say that if I ever try to learn R again it’s going to be through a YouTube tutorial, because trying the whole, “just start with a project!” angle was leaving me confused pretty fast.

Resumes were another thing I wanted to mention, for when you get to that point. Mostly this advice is going to be, do not do anything fancy. Single column, text only, and focus on hard skills over soft. Soft skills are communicated through the cover letter and phone screen.

I am not the best person to really talk about this since I myself am still learning the best possible way to go about this.

Communities of any kind are one of the best ways to learn. It doesn’t have to be the one I keep holding up– Women in Data– especially if you don’t identify as a woman. There are so many ways to find communities. Slack channels, subreddits on Reddit.com, Discord channels, groups on Facebook. If you can get into a community that’s data focused, you’ll be around like-minded people, a good amount of whom are likely to be in the same position as you, or at the same point in the transition as you are.

I want to revisit the Reddit.com idea. When I was in the residency program, I joined r/dataengineering to get a better idea of the process. r/datascience gives you a deeper look into the industry there, but also the expectations and what the job turns out to be. These are filled with people who are also doing the same thing you are. I do want to caution though that they don’t always have the nicest people. I tend to lurk and read threads and posts more than making them myself.

Although, r/girlsgonewired tends to be a good space, and it’s for all tech roles, not just data.

Overall there are just a lot of resources. In the subreddits you’ll find they each have their own wiki with links to websites on where to learn. They all also have stickied posts that are usually filled with FAQs, start there. A lot of channels on youtube have the same, they’ll have playlists for specific things and sometimes for projects.

This post ended up being about the importance of communities and searching and using any and all resources you can think of to achieve your goals. I think that’s the heart of what I want to get to with this entire series: programming and by extension working on data is one of the cheapest things to learn for all of the resources that exist. It’s like telling yourself you want to learn how to run. Provided you have clothes to run in and some shoes, you can start.

Programming is the same: an internet connection and a dream will get you where you want to go.

Another thing I want to mention: “thinking like a programmer” is also a skill you’ll need to work on if you’re just beginning in this space. It’s hard and it takes time, but ultimately it comes down to having the patience and understanding to break down all the ways you know how a problem can be solved. It’s not always a fast process.

I found “Thinking Like a Programmer” in my library, and it helped me reframe my mindset. Again, it isn’t an overnight thing. If you have the googling and the searching down and know what kind of resources you’ve got to solve a problem, you’re already a good chunk of the way there.

Programming, and data analysis, engineering, and science by extension, won’t give you instant gratification. They’re slower, deeper processes that will teach you something new every time. But I hope that you find thrill and excitement in them, in unearthing findings and revealing things about the data.

I hope, most of all, that you stick with this, and that you find something amazing that keeps you going.

Thank you all so much for joining me for this series! May all your learning be enriching and fun!