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It wouldn’t be wrong to infer that the modern era is ruled by data—both raw and actionable, with our travel plans, educational initiatives, and shopping habits manipulated by this extremely potent entity. With every online and offline activity generating humongous amounts of insightful data, it is appropriate that professionals devise extremely targeted techniques for assimilating, analyzing, and amalgamating the insights. MS in Data Science is, therefore, ideal coursework that would allow me to progress in this extremely niche domain besides deploying the concepts of engineering, computing, mathematics, and business for developing functional problem-solving skills. With a master’s degree in Data Science, I can help diverse industries and sectors like healthcare, insurance, management, and banking in developing strategies that work. Lastly, with online streaming vendors like Netflix making use of customer data for creating customized recommendation engines, it is extremely fascinating to delve into the world of Data Science with Analytics and other technologies to rely on.

While I primarily talked about the target points leading to my course selection, what motivated me the most is my undergrad project selection! The moment I took up and started exploring more about predicting cyclones with Machine Learning at the helm, I slowly started realizing the true power of data. What piqued my interest further was how the data sets were treated before putting to use, concerning normalization and outlier removal. I started learning that every moment can be predicted, provided the available data sets are procured, improved upon, and used for deriving visuals and insights. Not just that, another motivator was the Kaggle website which did clear out my concepts regarding Data Science as a domain.

It would be extremely appropriate to talk more about my undergrad degree program, specifically in terms of domain selection, subjects relevant to my MS program, and the major motivators behind the same. To begin with, I started with a Bachelor’s in Engineering with Information technology as my domain of expertise. During the coursework, I invested a lot of time in subjects like Design and Analysis of Algorithms, Software Testing, Database Systems, Object-Oriented System Development, Data Warehousing, Computational Intelligence, Information Security, Digital Image Processing, and more. In addition to that, I also indulged myself quite actively towards learning more about Python, Java, Social media analytics, Mobile Computing, and Big Data Analytics. My inclination towards IT as the preferred domain of study comes from the fact that computing technologies have always intrigued me. Since my formative years, I was extremely optimistic regarding the deployment of these concepts concerning the Software Industry. Therefore, when I finally got an opportunity to unravel the applications and mysteries pertaining to this sector, I embraced Information technology with open arms and with an open mind.

It would be wrong to put every undergrad topic at par when I was slightly more inclined towards subjects like Big Data Analytics, Web Programming, Programming Languages, Data Structures, Data Mining and Warehousing, and Design and Analysis of Algorithms. Not just the theoretical aspect of these subjects, I even took a keen interest in the practical applications of the same during the lab courses. The willingness to study and learn more about the unexplained helped me qualify as one of the top class performers.

The projects taken up by me do require a special mention and I would like to enlist the more relevant ones as a part of this discussion. The undergrad project pertaining to Cyclone Prediction spanned across a period of 6 months and made use of Machine Learning, Java, and Python as the associated technologies. During the project, I actively collected relevant meteorological data and put them to use, while deploying ML technologies on the way. This helped create a predictive engine of sorts, thereby assisting users with trend analysis and data visualization. In addition to that, I also took up projects related to online shopping web application using MEAN stack, CBIT Clubs using Polymer Web components, and Courier Service creation C language as the underlining concepts.

My undergrad thesis was therefore focused on the most relevant project I took up during my coursework i.e. Cycle Prediction using Machine Learning. This project primarily targeted cyclone predictions where the concerned individual was required to input the available data and incidences for the existing algorithms to work. While insights could still be procured, the project did involve data cleansing techniques for improving the accuracy of inferences and deductions. The results were followed by a detailed prediction graph. In terms of internship and industrial visiting experiences, my short yet rewarding stint at the Ashira Labs deserves a special mention. The one-month long internship program helped me understand more about MEAN stack web development while making way for deeper insights in regard to Node JS, Angular JS, MongoDB, Express JS, and other involved technologies. Apart from that, I also gained a lot of relevant experience by mentoring freshers at the workplace.

Now when I have mentioned workplace mentoring, it would be inappropriate not to talk about my work experience. For a year or so, I was associated with the NCR Corporation in Hyderabad, a company that concentrated solely on Woolworths Australia; thereby devising checkout solutions for the concerned firm. During my work tenure, I learned quite a lot regarding customized professional development requirements, automated testing, C++, C#, and Agile Methodologies. My association with this product-centric company allowed me to understand more about the existing technologies and their implementation in regard to the Travel, Finance, and Retail sector self-checkout options. In a nutshell, my work experience has been extremely fulfilling and I also had the opportunity to interact with professionals from diverse educational and cultural backgrounds.

I realized that pursuing MS in Data Science would come forth with a lot of rewarding opportunities especially when the career goals and industry-specific implementations are concerned. As every sector requires data visualization to draw actionable insights and increase existing revenues, Data Science comes across as a highly relevant domain of study. For me, however, a Master’s Degree in Data Science would help me realize the short-term goal of proper resource utilization pertaining to a specific industry. The long-term goal of working alongside a company of repute is also possible to achieve if I can fulfill the responsibilities and rigors of this international Data Science curriculum.

Besides academics, I would also like to talk about my extracurricular indulgence where I bagged prizes in singing and story writing competitions. The leadership aspect, however, needs to be discussed in detail as I was the elected Vice President of the social wing during my undergrad degree program. These skills, however, were carried along as I successfully led a three-member team to the Hackathon. I was also an active part of the company CSR which concentrated primarily on educating the underprivileged kids from different walks of life. Moreover, I was also elected as the acting Vice President of the College Social Service Initiative which concerned blood donation, plantation drives, and Swachh Bharat (Keep India Neat & Clean) Campaign.

I firmly believe that if professionals are interested in enhancing their problem-solving skills and technical prowess, pursuing MS in Data Science is the best way forward. With Walmart collecting almost 2.5 petabytes of data on an hourly basis, it is quite right to infer that Big Data and the applications of Data Science are growing at a rapid rate. If given a chance to pursue Master’s in Data Science from, I would be able to help businesses make profitable decisions in the future by putting the concepts of Big Data to use. With Data Analytics to work with, I will have the ability to manipulate the existing organizational parameters in some of the more prudent ways. Moreover, my academic skills, work experience, and other credentials would help me understand the international Data Science curriculum in a much clearer manner. I would, therefore, be an asset to the university and would request you to give me an opportunity when it comes to pursuing Master’s in the preferred domain of study