This is my adventure.
This is my adventure.
The Paradox of Choice9 min read
I’m not a fan of buffet style dining, especially if it’s brunch. I mean do you pick the breakfast items or the lunch items, maybe a bit of both? My problem is I usually like some from each and no matter what I choose to eat, I feel like I should have picked something else. Forget about diner menus; they’re just as bad. I would be much better off if I had a few selections to choose from or better yet, someone recommending what choice I should make.
The paradox of choice: the more choices there are, the less satisfied and less decisive we become. Can also lead to analysis paralysis.
There are over 100 coding bootcamps and dozens of learn to code websites both free and paid. Do I want to learn to be a data scientist, data analyst, frontend developer or full stack developer? Maybe user experience? Then there are the programming languages, some with interesting names like Hadoop and Python which was named after Monty Python’s Flying Circus. Anyone remember Monty Python and the Holy Grail? I’m starting to feel like I’m on my own search for the Holy Grail.
I began my quest by choosing a Data Science foundations track on Cognitive Class, formerly known as Big Data University. The classes were free and I thought they would give me a taste of what a career in Data Science would be like and whether it would be a good fit. Everything was going great and I was enjoying learning the theory behind data science but then came Python. I would watch the video and pause it so I could write down what the instructor said but by the time I got to my notes, I had already forgotten what he said. Back and forth, back and forth and nothing was sticking in my head. Had my brain shrunk that much?
Then I remembered that when I was in school, I learned the most when I studied the textbook. Teacher lectures didn’t hold my attention and I often found myself doodling in my notebook. Ok so I’m not a good listener but I can read. I did a Google search for Python for complete beginners and I found a great book online called Automate the Boring Stuff with Python. It breaks Python down into the simplest of terms and it allowed me to digest the material at my own pace. I felt like I was starting at the pre-school level but if that’s what it took for me to learn then so be it.
I also found a neat website called Sololearn. It’s a gamified way to learn Python. You solve problems and move up the levels to earn badges. It’s not really in-depth but I figure it’s a good supplement. They have an app so I can practice anywhere! I’ve been using it as my end of day practice along with a glass of wine. I figure it’s a much better use of my time than aimlessly surfing Facebook and Instagram. I also found a good Python class on Dataquest that was less video and more interactive. Plus you can download the key takeaways from each section.
Unfortunately, I kept finding myself getting stuck as the problems became more algebraic in nature. Since there were so many Python classes online, I figured if I got stuck I could start a new course to see if the concept was explained differently but I realized that by constantly looking for something better I wasn’t getting anywhere.
If I only had one choice I would have to either suck it up and figure it out or quit. By constantly looking for something better I wasn’t getting better. It’s a perfect example of the paradox of choice.
So I took a step back. If I was going to keep having an issue with the math, then maybe I should work on that first and go back to Python at a later point. That meant linear algebra and statistics. But was this the right way to go? I looked through a number of job postings for data scientists and data analysts and I started to get discouraged. Despite reading several times that you don’t need a masters and/or phd to become a data scientist, the majority of postings listed at least one of those as a requirement along with a strong quantitative background. I didn’t like the idea of spending all that time learning math only to find out I didn’t have the right degree. I remembered a link Kim had given me about coding. It was the one link I hadn’t checked out so I figured why not, maybe it would help point me in the right direction.
“Learn to Code in 2019, Get Hired and Have Fun Along the Way” sounded interesting. While I wasn’t an expert coder, I knew my way around HTML and css. I liked the “get hired” part and if I was going to have fun then sign me up! The author teaches a course on Udemy that mirrors the article called “The Complete Web Developer in 2019: Zero to Mastery.” I figured I could use this course as a backup in case the data science course didn’t pan out. I signed up and started to feel hopeful again.