By - Dheeraj Pranav, Board Infinity Alumni

My Story

Today I want to share my story of how I was able to develop a passion for Data science, machine learning, and learning every day.

If you don't like to read you can watch my Career pe Charcha Episode for full review.

So a bit of my background… I’m doing Computer Science Engineering from Hyderabad. I’m in my last semester right now, haven’t been able to complete it due to the whole pandemic situation.

My entry in Data Science

My story starts after the end of my 6th-semester exams. I was just looking at the new subjects that would be taught in the 7th semester. I realized that a lot of the subjects in the 7th semester were data science-oriented; subjects like data analytics, Python, machine learning, and data mining.

Data science had been receiving a lot of hype from media during that time. I had no idea what these subjects were, so I decided to start exploring a few articles and blogs. I wanted to learn more about Data Science, I was curious. My main reason was that, if I learned about it now, it would prove to be helpful for my 7th-semester.

By researching on my own, I actually learned a lot about data science, but after some time I hit a barrier. I had registered for a ton of blogs, newsletters, and articles but Data Science is such a huge field that sometimes you just don’t know where to start. There were certain things that I couldn’t completely understand and I was left very confused. I felt like I needed some proper guidance.

There was absolutely 0 hands-on learning in my college, so I knew the concept of coding but I wasn’t very good at it. It was more of just knowing a few lines of important code that would help me pass the exams.

I took an online course but they had the same learning methods as my college. This institute offered pre-recorded lectures and absolutely 0 hands-on experience. By the end of the course, I felt like I had learned absolutely nothing, except maybe a bit of Python.

I felt like I needed a mentor who would tell me which concepts to learn first and which ones to learn later. At this point, I decided to join Board Infinity’s Data Science Learning Path.

My BI Learning Experience

Board Infinity’s data science learning path focused more on hands-on experience & had a lot of assignments. I had to keep researching various methods to solve the assignments, this led me to explore more in my free time & exposed me to a lot of practical experience. This kind of hands-on teaching allowed me to accelerate my learning rate by a lot.

The Board Infinity experience was just completely different. Being able to attend LIVE classes and interact with the mentors/coaches was very different than just watching some pre-recorded lectures. It’s was also very easy to get my doubts cleared from a coach (they were just a message away) and interact with them.

I had learned so much from this course, that during my 7th semester Python lab exam I was able to finish faster than anyone else in my whole class. It led me to develop a new passion for coding and data science. For the first time in my computer science degree, I felt that I was actually able to understand the code. It actually felt like I was actually learning the concepts instead of just memorizing them.

Before taking this course, learning would just seem very boring to me. But Board Infinity was somehow able to reignite my passion for learning, I truly enjoy it now.

Where I got the Job?

I also got placed at Applicate AI through Board Infinity. I’ve started working for the company as a Machine Learning Engineer. Now, I learn something new about this field every day, I love it!

That’s it.

That’s exactly how I managed to land a job as a Machine Learning Engineer in about 6 months.


Connect with Me

I hope you liked reading this post and I was able to provide some value to you. Feel free to connect with me by  filling this form. "Connect with Board Infinity Alumni"

Have an amazing day!

You can also watch fellow learner experiences on Career Pe Charcha live series on Board Infinity's Instagram Page.