I began my Data Science journey back in 2018. I studied math and python through YouTube and a bunch of other free online resources. Using this newly acquired knowledge, I tried to get into a Data Science bootcamp called Galvanize. I failed the exam on my first try. I’m glad I did because that taught me my first lesson in Data Science-
Practice what you learn, implement it on your own
Earlier, I was staring at YouTube video and blogposts, trying to memorize different concepts associated with math and Data Science. Neither had I implemented concepts or practiced what I was learning.
On my second attempt at the Galvanize admission test, I was able to use the different methods that I learnt by practicing over the last couple of weeks.
After my successful 3-month bootcamp at Galvanize, I discovered my yearning towards Natural Language Processing or NLP in short. NLP is basically text processing, i.e., teaching AI models how to interpret text.
NLP was under-utilized back in 2018 (and is still kinda in a few domains like the energy generation industry), so an added benefit was that I could learn and continue to grow in this field.
My first job was at a startup called Proximate.io, where I was working on NLP based Data Science pipelines which dealt with classifying emails into hot/warm/damp/cold sales leads.
I worked here (remotely) for around 4 months, and had to leave when we weren’t able to secure enough funding to continue.
My next job needed me to relocate to Columbus, OH and it was with Ventech Solutions - a company which was looking to transform the smaller clinics in the healthcare domain by digitizing their data and introducing Statistical or AI solutions.
To give you a tl;dr of my time at Ventech,