I am from a Biological science background. I did my B.Sc in Advanced zoology & Biotechnology and M.Sc in Bioinformatics. I was an average student in my school days, and for some reason, I hated math, but ironically I’ve chosen a career path where math plays an integral role. Learning concepts out of my interest is quite challenging, but it gets interesting to dive deeper once the intuition behind it is understood.
As soon as I completed my Master’s, I started looking for jobs, but the second wave of COVID made it worse, and there were very few jobs that were of relevance to freshers like me. That is when I decided not to waste any more time and upskill myself.
The biggest challenge I faced with pursuing Bioinformatics as a career was the requirement of a Ph.D. to get a better edge in the industry, as it is more into research and development. In my opinion, that career path of investing an initial 4-5 years in a doctorate before starting one’s career seemed quite long. There were other complicated factors involved that waved a no signal for enrolling in a Doctorate.
My choice of college major was purely based on my love for Biology. Lesser did I research about its future career prospects and job opportunities in India. The career paths one could take up after graduating from biological sciences were very limited. Bioinformatics was an elective paper in my 4th semester of UG. Being a blend of biology and analytics, Bioinformatics felt like an apt choice to make a drift into the tech domain. Data science is a much wider umbrella with enormous growth potential, fast-paced technological advancement, and job openings in diverse sectors. I wished to change tracks and be part of the data revolution that’s happening.
Coming from a non-technical background, I doubted if I could make it into this highly competitive field of Data Science. PGP-AIML gave me the confidence and made it happen. I received a message from HR on LinkedIn regarding an opening for Data Analyst at Predigle, which is an AIML based Startup Company. I applied with my resume and got a call for an interview. A general HR interview phase followed by a technical interview phase happened. The interview was focused mainly on Machine learning algorithms & techniques. Since PGP-AIML covered most of them in the initial 4 months, I felt more confident in the interview. The following day I received the offer letter for the position of Data Analyst.
I have attempted to learn AIML by myself, but the consistency to stay on track was quite challenging. PGP-AIML made sure that I accomplished my learning goals by being flexible and work-friendly. This journey wouldn’t have been possible without my dearest guide Mr. Saravanan, who is a guiding light for my career and my supportive parents.
The course curriculum was very well structured, with quality supplement materials and hands-on activities in addition to the lectures. The lectures were to the point, and all modules were properly paced to aid intuitive conceptual understanding. Most modules had this add-on content along with the mainstream lectures making room to advance a technique and dive deeper. The mentoring learning sessions made learning interactive, and the weekly case studies discussed over there helped look at a business problem through the data lens.
I am feeling really blessed to have made the first step in my career. I am looking forward to an incredible learning journey, building data-driven solutions. There is no ultimate goal that I have pre-planned. I am a person who goes with the flow. I believe smart work and a thirst for learning will take you to greater heights.
Making a career transition decision might be hard. But with one’s willingness and interest, the changing of tracks becomes less of a burden and more inquisitive. This domain is very vast. Learning one thing after another (starting with linear algebra, hoping to finish it fully and then start with python, then move onto ML, etc.) can be a little overtiring. A top-down approach of learning on the go would rather help a lot to assess one’s pain points. Being part of Data communities on LinkedIn, Discord, Slack, Twitter, etc., has helped me stay up to date with the fast-evolving tech. These communities open up to a wide world of opportunities and are a great place to network and work on real-time projects. Smart work, dedication, and consistency would definitely pay off.
