SOP Sample for MS Data Science in the UK

Statement of Purpose

"When working with data, I discover what I really want to say."

As a curious middle-schooler, I always had a tryst with science and technology. Learning about the works of [NAME] and [NAME], the godfathers in the field who laid out the brilliant schemes of using backpropagation to train neural networks on data, which later became a keystone for all neural network successes to date in machine learning, has taken a massive leap, leading to some incredible technological breakthroughs like the generative adversarial network, which builds two neural networks that are "divided" against one another to create an illusory image. Witnessing these baffling scientific discoveries, particularly in the field of machine learning, sparked my interest even more. As an upshot, I decided to pursue a B.Tech in Information Technology at [UNIVERSITY] in the year 2018. Henceforth, I embarked on a journey that impelled me towards my goal of engineering solutions with a social conscience for problems that arise from core cognitive errors due to several functional limitations of humans.

Besides the curriculum, I enrolled in various courses given by [COMPANY], [COMPANY], and [COMPANY] in the spectrum of Python, Tableau, and Artificial Intelligence Foundations respectively. Following this, I have also enrolled in a PGP program at [UNIVERSITY], with a specialization in Artificial Intelligence and Machine Learning, earning the epithet "Jack of All Trades" for my remarkable performance, with a GPA of 3.97 on a scale of 4. Furthermore, I have earned certification after my competence has been tested in a wide range of skills such as Python and C by [COMPANY], and Data Science by [COMPANY].

I translated all the acumen gained in the subsequent projects I undertook as part of the curriculum and the internship projects at [COMPANY] and [COMPANY]. To mention a few, my first project at the former was on "Text cleaning algorithm", which was designed to clean scraped news items by removing advertisements and other irrelevant information. It removed the advertising with a 70% accuracy rate and was successful in removing all other contaminants in the text. Another vital project, termed "Hybrid recommendation system", was created to sort articles based on a variety of criteria, including the user's activities and demographics. As a part of that, I conducted an "exploratory data analysis" to find all of the features that may be used to create a hybrid recommendation engine.

The three distinct projects I worked on as a data science intern at [COMPANY] provided me with a deeper learning experience, two of which were utilities that helped the team reduce time consumption and eliminate repetitive tasks. I was the only member along with my manager to be a part of a pilot project with a global client, "[COMPANY]" ([COMPANY]), which is an alliance of more than 50 top firms such as [COMPANY], [COMPANY], [COMPANY], and [COMPANY]. The project's mission was to detect the causal factors of pregnancy complications and to predict future pregnancy complications.

In brief, I had already spent more than two years in the field of data science, had completed the PGP course, worked for 1.5 years at two firms, and had opted for data science electives such as machine learning and natural language processing, as well as computing, during my undergraduate program. And I am glad to report that in the firms where I interned, I was hailed as the "youngest yet sanest, and the go-to person". In addition to being an "[COMPANY] certified software programmer", all of the above mentioned was accomplished while still pursuing undergraduate courses at the university and maintaining a CGPA of 8.5.

I feel that listening to music, playing cricket, and reading fiction books help me unwind outside of my academic life. In addition, during my collegiate years, I was able to master my teaching skills by taking classes on "Fundamentals of Machine Learning" to the freshmen at my university, which resulted in refining my competence for articulating complex knowledge simply and intriguingly. Reflecting on my academic journey, I can say confidently that the academic program specializing in artificial intelligence with machine learning has bolstered not only my academic performance but also my overall personality by fostering my cognitive skills ranging from problem-solving to higher analytic thinking, all of which are aided by my innate creative impulses.

The recent technological inventions in the stream of data science are spell-binding beyond belief. Discoveries range from using data fabric as the central architecture, allowing effective cohesion of hardware and software, allowing access across a range of locations both internally and externally without violating data privacy laws, to blockchain, which seamlessly integrates with the new cloud-based systems and can use data straight off the edge of IoT devices, piqued my interest.

I finally discovered two major challenges in the data science field. While the success of machine learning, especially deep learning, has enhanced the interest in data science, one must first prepare the data for analysis before using machine learning techniques. As the data life cycle's early stages are labor-intensive and time-consuming, data scientists spend over 80% of their time gathering, cleaning, and organizing information. I wondered what it would be like if a device could gather, clean, and wrangle the data automatically without a compromise on the model qualities like accuracy, precision, and robustness. After much thought on the subject, I decided to make this one of my major research questions.

The "behavior of primes and the Riemann hypothesis" is another area that piqued my curiosity. Prime numbers are the fundamental building blocks of all other numbers, and they are extremely important in a variety of fields that have a significant impact on our lives, including modern cryptography. Based on the Riemann hypothesis, all encryption methods allow us to make an online payment, log into our bank account, or even send an encrypted text message. Finding the next prime number and/or proving or disproving the Riemann Hypothesis can be made easier with data science approaches and cloud infrastructure like Azure.

Having stated my major research interests, I advocate the notion of one of the brilliant minds of the 21st century, [NAME], that "design is crucial to producing goods of high caliber". Hence, by researching the above-mentioned challenges, I would like to contribute my well-refined inputs in these areas, which I wish to analyze under expert mentorship at [UNIVERSITY].

With a modest level understanding of the subject domain, I could say that the profundity of the curriculum, inclusive of various subject domains by incorporating skills in data acquisition, information extraction, aggregation and representation, data analysis, knowledge extraction, and explanation, along with the research opportunities available in multiple areas at [UNIVERSITY], is perfectly designed to equip me for a career in Data Science. Hence, I am thrilled to learn from and work with subject experts like [PROFESSOR_NAME], and other expert faculty members by getting equipped with in-depth theoretical knowledge and the infusion of the right skills to conduct pioneering research in the areas of machine learning at a well-esteemed university like [UNIVERSITY]. Having made the statement of my objectives, I am looking forward to taking advantage of the varied opportunities to widen my horizon of chances in this field for an opulent career as a data scientist.