My graduate program at GMU is data analysis. It is a program of teaching how to collect data, analyze data and make a decision based on the data. As we all know, today’s society is stepping into the big data era. There is a great deal of ways for individuals, companies and the government to collect data and how to get useful information from the data is thus a topic that is worth digging deeply for whoever wants to find their own position in the future. Because of the widespread use of big data technology, many job opportunities exist from the fundamental level to the senior level. Studying useful skills is obvious the key to grasp good opportunities. In this semester, AIT-580, the introduction of big data is a primary course for us to step into the field of big data. It is like a review and introduction of the big picture of big data analysis, which is useful to provide an elementary concept of big data for me.
For my two pathway semesters, there are two data analytics core courses and four EAP courses.
INYO 501 | Graduate Transitions International Studies |
INYO 502 | Graduate Transitions for International Students 2 |
EAP 506 | Graduate Communication in Engineering |
EAP 507 | Graduate Communication in Disciplines 2 |
EAP 098 | English Grammar |
EAP Course | Language Support Course |
EAP 510 | Linguistics Capstone |
AIT 580 | Big Data to Information |
For my following formal study at George Mason University, I still have seven required courses to finish.
CS 504 | Principles of data management and mining |
STAT 544 | Applied Probabilities |
STAT 663 | Statistical Graphics and Data Exploration |
STAT 654 | Applied Statistics |
STAT 662 | Multivariate Statistical Methods |
STAT 672 | Statistical Learning and Data Analytics |
DEAN 698 | Data Analytics Research Project |
The concentration that I prefer to study further is Statistical Analytics., which will provide students with fundamental mathematical knowledge, for example, the course Applied Probabilities, and applied statistical skills, for instance, the applied statistics. This concentration can also teach me many things about statistical modeling, which is vitally useful for analyzing data and doing optimal decisions.
I like shopping. As the online shopping booms, I gradually switch into shopping online. Every time I open Amazon and Taobao, the most popular Internet shopping app, the internet can provide commodities that I am interested in. And the same as the advertisement shown on Twitter, Facebook, Ins even every webpage I open. I was curious about how they can know exactly what I am interested in and what I want. I think this is my first look of big data and it has been a kind of seed grown in my heart. Naturally, when it comes to me that what I should choose as my major for pursuing a master’s degree, I choose the data analysis intuitively. Now, I think I have a general big picture of my primary question. Every time we surf the internet, the history is recorded by the app as the original data of subscribers and all kinds of analysis of the original data, including your interest, your lifestyle, your fashion style and so on, are analyzed so that the app can propel the optimized context to subscribers.
My goals of the academic discipline are straightforward. First, which is also the most fundamental, is the GPA for my graduate study. I hope I can get at least A– for every course. Second, I want to find an internship next summer, so that I can accumulate some job experience. Third, I aim to study well how to fluently use R and Python to solve data problems, for the reason that programming is a really important tool in data analysis.
This semester, I studied four courses: EAP 506 is about how to write an academic paper, how to accurately cite references. The format for IEEE writing and the rhetoric method of reading a paper. EAP 098 is a selective course to teach students the grammatic model. AIT 580 is a data analytic core course to tell us how to use R and Python to solve data problems. INYO 501 is a kind, of course, to tell you how to adapt to American campus life for international students and know about American university culture and policy. Among these four courses, AIT is undoubtedly the most useful course for my major. As I mentioned above, programming is a very important part of data analysis. R and Python are two popular methods of data programming. This course is really helpful as well as a challenge for me because I never learned or even heard these two kinds of software before. In this course, I used R and Python packages to solve homework problems which are very helpful for my future job.