On a one fine day, I was going through some TED talks and I came across a TED talk named "The Best Stats You Have Ever Seen" by Prof. Hans Rosling. I was instantly intrigued by the fact that how meaningfully compiled Data can change the perception of someone. After that, I watched several talks related to Data and was amazed by seeing the amount of Data that we are generating every second and how we can leverage this Data to make informed decisions to make the world a better place. On that day, I decided that I would like to become a Data Scientist and work with Data, but I also realized that working with Data is an intricate job and requires advanced knowledge. With that in mind, I am applying to the Master's in Data Science program at XXXX University.
After I realized my career goal, I researched on how to become a Data Scientist and came across some best answers on Quora. I followed the suggestions and started learning Python Programming first and then transitioned into learning Machine Learning as it is the stepping stone towards my aspiration to become a Data Scientist. I joined the Machine Learning course by Andrew Ng and gained theoretical knowledge of ML. I like the practical approach to learning and as I got a basic idea of the subject I joined the "Machine Learning Specialization" by the University of Washington provided by Coursera as specialization is based on the practical side of ML.
During the "Machine Learning Specialization", I learned many technicalities involved in ML algorithms as I implemented many popular algorithms from the scratch. I developed and implemented these algorithms on popular data sets. I always get amazed by seeing the background process involved in making an algorithm efficient and accurate. For instance, how a small change in Learning Rate can make drastic changes in the solution of Gradient Descent Algorithm.
After the completion of several Machine Learning courses with great scores, I got noticed by Coursera. They invited me to become the "Coursera Community Mentor" for their ML courses. This turned out to be great for me as I got the opportunity to mentor students from around the globe and also improved my own understanding of ML algorithms as I had to go out of my way and understand these algorithms more deeply in order to answer their questions. I have been mentoring these students for the last 1.5 years now.
I also have a strong background in Computer Science as I have spent almost 6 years studying Computer Engineering. I have first done Diploma and currently doing B.E. and during this time I have gained a sound knowledge of core CS courses from Basic to Advanced level. I have maintained GPA of "First Class with Distinction". I always enjoyed the practical aspects of my studies, and that is one of the reasons why my marks in lab exercise, term work, oral examinations, practical examinations, and projects averaged above 85%. During my 3rd sem of B.E., I was down with Dengue fever right during the final exam time. My GPA was decreased due to this and I also got F in the subject "Digital Electronics", but I cleared that subject in next semester itself and also increased my GPA substantially.
I have done several projects based on ML to offset the theoretical knowledge I gained through MOOC courses. During my B.E. I had one course called Design Engineering which is a 4-semester-long project-based course. I developed a project named "Twitter Sentiment Analysis" which is a web application that I deployed live on the web. The project is about finding the sentiment of a tweet using the concept of NLP. I used Naïve Bayes algorithm for this project. I also got the highest grades in this course. I also like the interdisciplinary approach required in Data Science. A perfect example of this is my project "Music Genre Classification" for which I had to learn about signal processing because the entire project works around the signals generated by deferent genres of music.
As they say, Data is the new currency, I would like to be a part of this revolution by working as a Data Scientist. I would like to realize my aspiration by studying at XXX as the program has great coursework and is perfectly aligned with my interests. I will try my best to contribute to the overall atmosphere of the university. Thank you for giving your valuable time for reading my SOP and considering me for admission into Master's in Data Science program at XXXX.