“What we have is a data glut.” This quote
by Vernor Vinge, an emeritus professor of mathematics at San Diego State
University, has inspired me to purse higher education in data science since I
was in my third year at university. The abundance of data captured by the
modern powerful data analysis tools has brought a “data rich, information poor”
syndrome, which has further generated
an increasing demand for new techniques to effectively transfer vast quantities
of data into valuable and meaningful information. This has motivated me to
catch up with the advancements in the field of Information Technology and to
prepare myself to meet the industry standards. To this end, I intend to pursue
a graduate program in data science at University of British Columbia (UBC).

 

During
my undergraduate life, I have developed logic thinking, mathematical analysis, communication
skills and spirit of teamwork that are required to be a qualified data
engineer. With an intellectual curiosity, I have benefited from Engineering
program at UBC that has given me a comprehensive exposure to multifaceted courses
such as advanced calculus, principles of probability and statistics, applied
linear algebra and so on. Other courses like data structures and algorithm have
introduced me to different techniques to further explore more fascinating area
in data science. My proficiency in programming languages including C/C++,
MATLAB and Python has laid a solid foundation for my graduate studies. Through
a wide range of projects, from simple game design to drone flight control model,
I have successfully put conceptual knowledge into practice and gained in-depth
awareness about the significance of teamwork.

 

My two internships have intrigued and encouraged me to work towards
becoming an expert in this field. In my first job, I was employed as a quality
assurance Coop under the health check team at a company that offers data
management software and related services. This involved database, log and data process
monitoring. I was also responsible for identifying and reporting errors and
anomalies. As I became familiar with the process, I started to learn SQL by
myself and use it in order to access and manage data held in a relational
database. The job has provided me an opportunity to apply my academic knowledge
to solve real life problems, as well as allowed me to gain valuable industry
experience and an insight to the important role data plays for business
decision and financial progress. In addition, the second internship has cemented
my desire to be a data scientist and to eventually start up a data software
company after specializing in a business sector. Working as a research and
validation engineer, I have studied statistical machine learning on my own and
employed these algorithms using Python to study the behavior of vehicle
batteries in attempt to seek for a better method to predict battery ‘s state of
health. However, I realized the knowledge I possessed so far is not sufficient
to deal with the more challenging problems in the capricious world of technology. As a result, I
have decided to continue higher education in data science.

 

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