Please, meet Aaisha Muhammad, a 14-year-old Muslim Homeschooler from South Africa!
She is a bioinformatics and data science student. I got impressed with her passion for biology and science, and loved the way she approaches self-study on her own.
Read below her journey of self-learning data science.
What do you like the most about data analysis or data science?
My favorite thing about data science has to be how I can use it to get closer to my dream of being a scientific researcher! One of my major dreams is to be a researcher in biology and chemistry. Data science allows me to do bioinformatics and get closer to that dream of mine. I am not very enthusiastic about all kinds of data science – for instance, being faced with financial data or population statistics, or something similar is unlikely to appeal to me. But just the other day, I saw a competition come up on Kaggle for the human cells atlas project, and I was very interested and really wanted to join in. I strive to reach that level in my data science journey!
What was your first analytical project?
I’m still a student, and as a self-taught learner, I took some liberties and hopped my way through the DataCamp pathways, skipping boring sections (😉) and those which I already knew. Seeing how guided the pathway was, I am now trying my hand at more independent projects. I forayed into the Kaggle world, and promptly got stuck at the “Hello, World!” project – predicting Titanic survivors has thrown me off! So if that counts as my first project, then that would be it.
(Titanic challenge is so popular and a good DS start! Great work Aaisha! I did it too some time ago - Predicting Titanic survival using the most common ML )
For a self-taught student, what was the most difficult or challenging for you to learn?
Will I sound very smug if I say I didn’t find anything particularly challenging? (😉)
Are there more specific subject/topics which you find fascinating?
As far as topics in bioinformatics which I find fascinating, there are a lot of them! One of my most favorite things to explore has to be the stories genomes can tell. There is so much we don’t know about DNA that can be uncovered with data, and a lot of what we know about genomics has all been discovered by seeing the relationships via data analysis. There is so much yet to be discovered and I think it’s quite fascinating. A lot of it also has major practical applications in medical sciences, too – so while I’m mainly drawn by the scientific appeal, there is also a lot of human benefit to further exploration of this. It’s quite a vast field and I’m quite drawn by it all!
And what are your most used libraries/packages for Python/R you have to use a lot?
For the second question, I haven’t done much in R, and I haven’t really explored much the libraries in it. I mainly use Python. I think my go-to libraries have to be Matplotlib and Pandas. Data exploration covered by Pandas and the visualizations in Matplotlib are good enough to get a feel for what’s going on. Seaborn is good for the visualizations, too, and I do use it, as well. These three have to be the ones I use the most frequently.
What are the learning areas you plan to focus on next?
My main goal is to follow my bioinformatics and computational biology pathway. Alongside that, I find data visualization particularly interesting, and I’m dabbling in beginner machine learning too. I am still exploring all the various fields around data, and I might end up working in multiple dimensions alongside my bioinformatics.
Anything else you can advise or recommend to other self-taught students?
I don’t have much to say on this topic, to be honest! All I can say is that follow your passion, embark upon the journey that your interests lead you to. Just don’t underestimate discipline! Even if the interest fades a little down the way, discipline and determination will always carry through.
And secondly, never forget that you have an invaluable ally, to guide you through thick and thin – Google! 😉
Check out Aaisha’s website, which has most of her portfolio, both for data science and other projects: www.aaishamuhammad.co.za
And here’s a link to her Kaggle profile with data projects: https://www.kaggle.com/aaishamuhammad
I am excited and honored to have Aaisha as my reader, and can’t wait for the next discoveries and impact she will bring to the world of bioinformatics.