My identify is Praagya Vardhan Rathore; I’m a mechanical graduate with experience in Automobile design and growth. Throughout my school days, I’ve labored on varied automobile segments, primarily on Electrical automobiles, Autonomous automobiles, and Photo voltaic automobiles. Submit completion of my commencement, I’ve labored with Atom Motors, the place I Developed and initiated initiatives, together with managing prices, schedule, and efficiency. I’ve efficiently mentored greater than 2000 people and arranged greater than 20 automobile design and growth workshops in pan India, and in addition recognized plans and sources required to satisfy mission targets and goals by setting sensible timelines and checkpoints.
Mainly, after working with Atom Motors for greater than three years, I used to be extra concerned with how autonomous automobiles operate. This drives my curiosity in synthetic intelligence and machine studying. Contemplating that, I used to be on the lookout for a change in my ability set and my function, and therefore I joined the PGP-AIML program at Nice Studying.
Atom Motors was engaged on its new product, which is an Electrical cycle, so initially, the staff was engaged on market analytics and aggressive evaluation. The staff wanted a statistical evaluation on varied merchandise and the place we stood out there, and the aim was to establish the world of enchancment. For a budding startup Like Atom Motors, having perception over the newest EV, their specs like vary, charging time, and value will assist them to derive strategies that can hold them forward of their opponents.
We had been in a gray space the place we wanted to make choices analyzing just a few opponents in addition to analyzing our product. We weren’t positive about particular areas the place we wanted enhancements, however the aim was that we have interaction extra clients and be aggressive out there.
Superior knowledge analytics was the necessity of the hour which used know-how like EDA, ML and Information Scraping, and Information Wrangling.
The insights that our AI/ML idea utility introduced into the image was as comply with:
Mileage – We stand out on rank 19th out of 25.
Gasoline value/km of a automobile – we stand out 3rd final on this parameter.
Primarily based on the insights we gathered, we delivered many options on the totally different parameters corresponding to weight, charging time, battery capability, vary, and battery voltage of the automobile.
My suggestions and provided options had been sensible and data-driven, which was very useful for the staff. They had been extremely impressed with the insights and developments happening in these areas that supplied a much-required decision.
We transitioned from a static rule-based method to a dynamic, self-adapting, learning-based ML method in quite a few zones. We used ML to evaluate the price of information belongings, predict lacking worth, and ship cleaning suggestions, thus dipping the intricacy and efforts spent by knowledge high quality professionals. This lessens guide effort and governance actions.
As a Mechanical Engineer, it was a little bit of a difficult resolution for me to have such a drastic profession change. Although, I’m glad that I selected the appropriate path by becoming a member of the Nice Studying AIML Program. Being from a non-coding background, I used to be a bit nervous on the preliminary part, however the mentors had been supportive and sensible. The course may be very properly structured and extremely spectacular. The assignments and initiatives had been actually useful, which bridged the hole between theoretical and business data. I want to suggest non-coders like me begin their profession and upskill themselves within the area of Synthetic Intelligence and Machine studying.