3 lessons I learned as a first year Data Science grad student with no experience.
Even with college under my belt, Grad School has it’s own set of challenges.
This past year I started working on my Masters in Data Science. Besides taking a SQL class on Khan Academy and several math classes in college, I had zero subject knowledge. All I knew about data and analytics was that I was working in that department because of a part-time job I took in college. With that being said here are some lessons I learned outside of class.
1. Learning the skill is what matters, not the grade. Ever since we started school, we were taught that at the end of the week we would get a gold sticker (which later becomes grades and school lost a little bit of sunshine) for doing a great job. Even now in grad school, I find myself wanting an A in class, which isn’t a bad thing but distracts us from the real goal of actually learning the skill. It’s so engraved in our minds to get a good grade, that we lose track of what we are supposed to be learning. This is the reason why I decided to flunk my programming class and retake it. Full disclosure — my employer will pay for the class even if I don’t pass, which was another reason I went with the option since I have it. I was taking Intro to Programming where I was learning Python when things were going great; until we went into functions. For some reason, I could not wrap my brain around functions, and when we moved into classes and I could not keep up. At this point even with getting low scores on my assignments I was passing the class but, I realized this is the very foundation for Python and not fully understanding this integral part of the class was going to leave holes in my foundation. So I took an uncommon route and purposely failed it in order to retake the course. When I fully realized what I did my brain freaked out, especially when I saw my transcript but I know it’ll be better in the long run because I will have the foundation I need to be a great Data Scientist. Most people aren’t as fortunate to have the class paid for over twice, so my suggestion is in your free time (or really, designate a time) go back and dig deep into the areas you aren’t comfortable in. Don’t be afraid of starting over when you see everyone else moving on because what matters is having a foundation without any cracks!
2. Ask for help! Taking an online class has its challenges especially when the class does not offer any lectures and I needed help beyond YouTube videos. I started asking my friends who already have programming experience and I asked different people for help so I wouldn’t drown the same friends with questions. I rotated through my list so much I even got help from interns who already have computer science degrees. At first, it stung my ego a bit when recent college grads were helping me with my homework, but I got over it real quick though because I desperately needed help from a person and not just 3 min video. Moral of the story- don’t let your ego keep you from getting help! We all need S-U-P-P-O-R-T 😉. Plus, you don’t know who you’ll meet along the way.
3. Don’t psych yourself out that it’s too hard!! I was so nervous when I started learning the first programming language that I was messing myself up before even starting. I would preemptively worry I wouldn’t understand the homework that I was blocking my mental capacity from actually learning. My biggest lesson/ what I want everyone to know is that yes, programming is challenging and there will be more days where you wonder why you signed up for this, but that’s how I know I’m pushing myself out of my comfort zone and when you reflect on where you are, you realize how far you’ve come. ;)
Even with just one class complete, one failed and one a work in progress, I’ve learned more from starting this program in less than a year, than from my job the past couple of years. So just keep at it! I think the secret is perseverance and when you get that exciting feeling once you’ve solved the problem, you won’t want to stop! Plus, the thrill of figuring things out and creating new ones is the best part of being a Data Scientist!
