Leveraging the benefits of AI can help in moving up your career ladder and also help in optimizing daily tasks. Read further to learn about Renukadevi’s journey with Great Learning’s PGP Artificial Intelligence and Machine Learning Course in her own words.
I am an academician teaching statistics to Management students. I am currently associated with a leading B-School where we nurture the management skills of future managers and entrepreneurs. My core responsibility is to teach them the power of data and analytics for decision-making. We also have a team of faculty members who provide management consultancy services to several corporate entities. My primary assignment is to work on the data collected in that process. We realized that in the recent past, we had to work with large data on complex business problems.
As a statistician, I realized that I have to enhance my knowledge in Data Science. I joined and completed PGP DSBA with great learning. I was able to apply most of the concepts learned in the course at my workplace. I was able to deliver quality content to my students going ahead. We were also deal with critical business problems of our clients with the help of advanced concepts like predictive analysis, recommendation engines, etc. There arises the need to deal with more or qualitative data than quantitative data. The need to learn Artificial intelligence and machine learning became imperative. I started taking up the AIML course with great learning.
Recently, I was working with a chain of retailers who wanted to establish their retail outlets in various rural areas. As the target locations were located in rural areas, we had to understand the sentiment of the people in accepting such retail stores at their place, their purchasing pattern and power, and the fast-moving products. As this was a unique problem, where we needed to personally know the prospective customers, we decided to collect both quantitative and qualitative data by personally interviewing people living in those rural areas. The quantitative data collected through primary and secondary data sources were large, but as they were structured, we were able to easily apply several machine learning techniques to analyze our objectives. Data were also collected through interview methods and casual talks with people living in that locality.
We also had to deal with these unstructured data. As the data were media files recorded in regional languages, we used AWS to translate the data into English. Then we used NLP to process the data to understand the opinion of the customers, their sentiment towards the retail store in their locality, and the products they would buy in the retail store. Based on the analysis, we were able to identify the ideal location to establish the retail stores. As a pilot project, they have started their retail stores at five locations in the last six months.
Now, I have started using several AI and ML concepts in my research articles. I see a large scope for applying the concepts I have learned at my workplace. As research is one of the core responsibilities as an academician, I am seeing a lot of opportunities to apply AIML tools.
