whoami

Charles Di Renzo
Sep 2, 2018 · 3 min read
“silhouette of man looking star during sunset” by Benjamin Davies on Unsplash

I double majored and graduate in 2016 with a BBA in Economics and a BBA in Information Systems. I wanted to study economics because I knew that I wanted to start my own business someday and economics seemed like a great way to get a high level and low level understanding of how markets and businesses interact. I loved economics because you can look into a problem from both a social and quantitative point of view and then display the issue in either a paragraph of descriptive text, a formula, or a graph. Labor economics in particular personified a lot of the economic mindset of analyzing a market quantitatively then looking in to the societal causes behind the data. I decided to double major in Information Systems because I knew that technology was changing the way that we do business and the way that we live. The information systems major gave me insight into programming and databases, but mostly gave me a better understanding of how businesses use, develop, and analyze IT infrastructure to accomplish business goals.

Shortly after I graduated I began to investigate my graduate options and found a Data Science program that piqued my interest. As luck would have the University of Wisconsin started an online Masters of Science in Data Science Program that drew professors from each university in the University of Wisconsin system. Having the entire talent pool of the University of Wisconsin System is great because it prevents the departure of one professor from denying students the opportunity to take a certain class. It seemed like a perfect fit and a natural progression of my skillset, so I eagerly enrolled. I’ve just begun my courses to earn my graduate degree, but I’m excited about the journey ahead.

I’m currently working for a company that that does market research as a service. I’m lucky to be employed at a data driven company that I’m sure will be just as large a part of my education as my masters degree. Right now I primarily work with Unix and data analysis, but my role at the company is expanding and I’m sure that as I grow I’ll take on more complex and traditional data science tasks.


What do I know now?

The only class that I’ve taken at the graduate level so far is the Intro to Data Science and Communicating about Data Class. This class covered brief overviews of: the analytical process, statistics, machine learning concepts, visual analysis, regression, clustering, forecasting, relational databases and SQL, data science project management, and data governance. Whereas Communicating about data which includes the study of the nature, structure, and interpretation of data. Information communication topics include data visualization and design of data for understanding and action. Persuasive communication topics include the study of written, verbal, and nonverbal approaches to influencing decision makers. I also have some statistical and programming knowledge from my undergraduate degrees as well as self study.


What will I be learning and writing about?

I’ll be learning a little bit about anything and everything until I find an area of data science I’d like to focus on. For the time being, I’ll be posting about whatever I’m learning at the moment, this can change depending on my classes, my interests, and my work commitments. For example, lately I’ve been scripting things with python and unix to free up additional staff hours so I’ve been reading How to Automate the Boring Stuff with Python by Al Sweigart.

In no particular order I’ll be looking to flesh out my knowledge in areas of applied statistical formulas, machine learning, regression, bayesian analysis, building a recommendation system, as well as some data science tools like Spark and Hadoop.


How often will I update this blog?

It’s hard to say, but between a full time job, being a part time grad student, self-study and trying to have somewhat of a social life I’ll be trying to update this blog once a month.

A small independent blog about tracking my progress from rookie statistician to a senior data scientist.

Charles Di Renzo

Written by

Greenhorn Data Science
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