I am currently a Senior at Carnegie Mellon University pursuing a major in Statistics and I have completed a minor in Business Administration. Last summer, I worked on a NSF-funded educational data mining project at George Mason University’s Computer Science Department. The goal of my research was to identify the factors leading to dropouts from online courses. I analyzed Massive Open Online Course (MOOC) data from Stanford Lagunita’s Statistics in Medicine course, implemented various k-means clustering methods, and constructed a dashboard, entirely in R.
At the same time, I spend my nights and weekends working on side projects in R, some of which include hockey analytics, text mining, and clustering. Also, I was a technical reviewer for two Data Science textbooks: Data Science Foundations: Tools and Techniques and Deep Learning Illustrated. This experience strengthened my belief in the importance of data science education.
Additionally, I contributed to the advancement of online data science education by interning for DataCamp as a Content Partnerships Intern. There, I looked for potential instructors for DataCamp’s new courses.
At the end of the day, I aspire to become a well-rounded data scientist who achieves goals and is always willing to learn from other people. Please don’t hesitate to contact me at [email protected]