My name is Praagya Vardhan Rathore; I am a mechanical graduate with expertise in Vehicle design and development. During my college days, I have worked on various vehicle segments, mainly on Electric vehicles, Autonomous vehicles, and Solar vehicles. Post completion of my graduation, I have worked with Atom Motors, where I Developed and initiated projects, including managing costs, schedule, and performance. I have successfully mentored more than 2000 individuals and organized more than 20 vehicle design and development workshops in pan India, and also identified plans and resources required to meet project goals and objectives by setting realistic timelines and checkpoints.
Basically, after working with Atom Motors for more than three years, I was more interested in how autonomous vehicles function. This drives my interest in artificial intelligence and machine learning. Considering that, I was looking for a change in my skill set and my role, and hence I joined the PGP-AIML program at Great Learning.
Atom Motors was working on its new product, which is an Electric cycle, so initially, the team was working on market analytics and competitive analysis. The team needed a statistical analysis on various products and where we stood in the market, and the goal was to identify the area of improvement. For a budding startup Like Atom Motors, having insight over the latest EV, their specifications like range, charging time, and cost will help them to derive methods that will keep them ahead of their competitors.
We were in a grey area where we needed to make decisions analyzing only a few competitors as well as analyzing our product. We were not sure about specific areas where we needed improvements, but the goal was that we engage more customers and be competitive in the market.
Advanced data analytics was the need of the hour which used technology like EDA, ML and Data Scraping, and Data Wrangling.
The insights that our AI/ML concept application brought into the picture was as follow:
Mileage – We stand out on rank 19th out of 25.
Fuel cost/km of a vehicle – we stand out 3rd last in this parameter.
Based on the insights we gathered, we delivered many solutions on the different parameters such as weight, charging time, battery capacity, range, and battery voltage of the vehicle.
My recommendations and offered solutions were practical and data-driven, which was very helpful for the team. They were highly impressed with the insights and developments going on in those areas that provided a much-required resolution.
We transitioned from a static rule-based technique to a dynamic, self-adapting, learning-based ML technique in numerous zones. We used ML to assess the worth of data assets, predict missing value, and deliver cleansing recommendations, thus dipping the intricacy and efforts spent by data quality professionals. This lessens manual effort and governance actions.
As a Mechanical Engineer, it was a bit of a challenging decision for me to have such a drastic career change. Though, I am glad that I chose the right path by joining the Great Learning AIML Program. Being from a non-coding background, I was a bit worried at the initial phase, but the mentors were supportive and brilliant. The course is very well structured and highly impressive. The assignments and projects were really helpful, which bridged the gap between theoretical and industry knowledge. I would like to recommend non-coders like me start their career and upskill themselves in the field of Artificial Intelligence and Machine learning.
