Upskilling in Artificial Intelligence and Machine Learning can prove to be extremely beneficial for your career. Read further to learn more about Prasanna Venkatesh’s journey with Great Learning’s PGP Artificial Intelligence and Machine Learning Course in his own words.
As far as my professional background is concerned, I started my career as a market research executive, working on data collection and cleansing projects for best-in-class market research organizations like Kantar IMRB, IPSOS, and Kaybase. Later on, within a year, I started leading market research teams and project coordination for internal and outsourced teams. After 3.5 years working in the market research domain, I joined a Waste Management Company as a Research Analyst and moved on to Managing Live Projects and Digitisation projects for the company.
Before joining the PG program, I was working as an Associate Coordinator in a Market Research Company and was self-learning Python and VBA Programming.
As I was working hands-on with data, I was also researching what else I could do with the data at hand, and that’s when one of the co-founders of the company suggested that I look into R Programming and Data Science. Eventually, with a bit of research, I found that AIML is one of the leading technologies being followed that has a lot of room for innovation. My long-term goals were also very much related to innovation, entrepreneurship, and Information Technology. As a first step towards the industry, I decided to take on this program.
My capstone project is to let end-user find where their valuable objects are located in their house or industrial workplace. The idea for such a capstone came simply from my daily habits and observation. Generally, during a crunch of time, we end up searching for our daily use objects at home and end up getting frustrated at not finding them on time. My goal through the capstone was to see what could be built out of such an idea. One of the main pain points was to find out the complexity of the project after choosing the idea.
After finding the complexity, we started researching more and building upon programming skills and algorithms to get to the point of understanding the problem and how we can scale it to a proof of concept.
Mentors are the ones who have done it all and know a lot more about the projects that we have taken up. Our mentor was able to get us to know what the basics for our project were and motivated us to get hands-on work done that laid the foundation for the rest of the project.
The impact from the capstone project is all internal. We were able to improve our own programming skills, using various libraries, learning the building blocks of various algorithms, and most of all, we learned the approach to solve problems on our own, which will help us the most in the days to come.
From the time I started the capstone to now, I can clearly see the difference in my own potential to efficiently understand complex concepts, and moreover, I am able to internalize more and more of previously learned concepts and connect the dots to overall improve myself as a Programmer as well as an AIML practitioner.
Analytics is vast and very interesting. The possibilities of what you can achieve with analytics are endless. I advise all starters to read a lot of codes, read a lot of documentation, mimic codes, make tons of mistakes and build a lot of projects. Learning the concepts behind the functioning of vastly used libraries and algorithms will definitely give you an edge in your analytics journey. More than anything, approach the program with a mindset of creating something new, something that you always wanted to build. That excitement itself will keep you motivated and always on edge to learn more and more and more. Lastly, if you are new to analytics, take your projects seriously and make the most out of them.
