The Journey So Far: Becoming a Data Scientist
Whoosh! the Hamoye Data Science internship ends in a few days. Has it been a ride? Absolutely! This is an attempt to summarize my experience over the past six months as a Hamoye intern, and I hope you take something away from here.
Prior to the commencement of the internship, I had no experience whatsoever working with the Python programming language, and as a matter of fact; I had only just begun coding with SQL, and had only a couple of weeks of experience under my belt. I was much more familiar with tools like Excel, Power BI, and SPSS. Python used to feel higher up the order, not saying it isn’t anyway :). However, knowing that it was going to be the chosen programming language to be employed during the internship, I knew things were about to get real. Having to research started quite early for me because I was confused as to what track to register for. At the time, I couldn’t make a clear distinction between what each track entailed. I later decided on the data storytelling track though, because it seemed closest to what I could relate with.
Fast forward to when coding started in full force: I must confess, it felt like gibberish and it was a struggle. I didn’t make the 75% pass mark for the first two stages, and I thought it was the end of the road for me with Hamoye, but then the leaderboard system was adopted instead. In all sincerity, that was a move I am particularly grateful for because it preserved the interest of beginners like me, who needed time to adjust. Eventually, I was able to pick up the pace and improve as the internship progressed. The whole definitely turned out to be greater than the parts for me.
During the orientation phase, we were encouraged to help others by giving answers to questions, and generally contributing when others needed help. I was fired up, ready to supply my colleague answers back to back, little did I know that in the earlier stages, I would be needing more answers than I could have thought of providing. Coming from a social science background, I was confused about the littlest of things. I had questions such as; why is the function of this bracket “()” different from that of this “[]” bracket? I had issues understanding how to correct the simplest kinds of errors e.g. syntax errors. I would spend hours trying to figure out what was wrong with a line of code, get tired, take a break, get back to it again, rinse and repeat.
Searching the web wasn’t yielding much effort. Anyway, I realize now that I wasn’t even using the right search terms, and I can laugh at my mistakes now but it wasn’t at all funny at the time. I also believe another reason I got better was the fact that I was unwilling to just copy and paste any random code from the internet just because it works. For instance, I wanted to understand why the word “join” is in the code or why there is space before the “.” Also, participating in the “100 days of data science” helped me to a large extent because it meant that I had to learn something new every day for me to be able to make a post.
At least, I can now very well distinguish between what the different tracks entail. Data storytelling, simply put, involves the use of visualization and narration to explain the jargon of data, in such a way that the layman would understand. Moreover, to explain something to others, you have to understand it first. I have the opportunity of working with various websites and sophisticated tools, such as Jupiter notebook, google Collab, Kaggle and Github to form collaborations, model, analyze, visualize, preprocess, and scrape data among others; most of which were also firsts for me.
All I used to know about the Panda is the fact that it is an animal. However, these days, each time Pandas come to mind, I am importing it as pd :)
I have come a long way from where I started, but I am still nowhere close to where I hope to be. However, one thing I am certain of at this point is that “practice makes perfect”, and maybe the other half of the expression should be…“and builds confidence”. In other words, never stop learning!
