As a Junior at Northwestern University at Evanston, I am pursuing a major in Data Science and minor in Business. Each Quarter, I will write about my experience with the Data Science program I am part of.

I just completed the Winter Quarter of my Junior Year at Northwestern University, my first quarter back on campus after a fulfilling time living abroad in Madrid in the Fall. This quarter was an academic adjustment, as I loaded up on a variety of Data Science classes to prepare me for my internship and career. 

Despite the difficult course load, I felt I learned a lot this quarter that will apply to my future. The courses I took were: Linear Algebra, Statistical Theories and Methods, Data Visualizations, and Accounting. 

I will write detailed posts about each of the data science classes I took. Here’s the summary:

Data Visualization

• Using R and RStudio
• Utilized ggplot and shiny to complete a variety of assignments
• Had taken a class with R before, but was my first time being able to apply it to a data science setting 
• Created maps, experimented with themes, annotations, coordinates etc. with ggplot
• Apps and dashboards with shiny
• Final Project: Used ggplot to analyze Airbnb data. Created 3 plots:
  • Average price of apartments and houses based on location
  • Density of ratings based on location and property type
  • Average price based on years of being a host on airbnb

Statistical Theories and Methods

• Different types of distributions (Poisson, geometric, normal, binomial, etc.) and their applications
• Probability methods
• Would have liked to see the applications to data science a bit more, hopefully that happens in the next class in the sequence that I take
• Will cover this in more details in part 3 of this series

Linear Algebra

• Matrices and operations using matrices
• The concepts of linear algebra are critical for data science applications. The key concepts are used for data presentation, model building (e.g., linear regression) and model interpretation, dimensionality reduction (e.g., principal component analysis)
• Will cover this in more details in part 4 of this series

Accounting

• Business perspective
• Can allow me to understand financial data in my internship, especially if I am required to make decisions about whether a particular product or service is good for the company
• Insight into how businesses make decisions when it comes to finance and banking