Often, skills that seem unnecessary are the ones that define success. Given a choice, you would prefer to take the longer part, as it may look like a daunting task to learn that underrated skill. Getting into Data Science requires a lot of skills, even to face an interview. Thew…

It’s effortless to get lost in just consuming content. It gives us the feeling we are making progress. However, that is far from the truth. There were two different modes of operation I tried: one where I continuously learned and others where I applied what I learned. In the first case, the retention rate was less as I lacked the significant experience to store the knowledge completely. In the latter case, I was able to make faster progress and even retain better.

I started my career as a “terrible” Data Science trainer. It was not easy, teaching as a fresher. Back of the mind, I always had the feeling of being an imposter. How can I teach someone without experience? However, I had a super-strength which I did not know back then. …

Learning Data Science (or any other subject) is not linear. Reading one book from page to page or watching an Online Video course video after video may not be the best way to learn. Try non-linear way of learning. Read or watch a few pages/videos, implement what you learn, fail, get stuck, research and then read or watch again. This way, you will know what is required for you to master a subject until you can implement quickly.

“Your real self may be hiding somewhere, look for it within, when you find yourself, you can freely be what you want to be.” ― Michael Bassey Johnson Both eastern and western philosophies will hint or urge you to look inside yourself to find yourself. …