"It was an interest I had since completing
a Marketing Analytics certification
during high school"
The opportunity arose in college, to merge the prevalent intersection between data analytics and marketing.
As a result, I took three Data Science Academy (DSA) courses that rapidly enhanced my knowledge.
(DSA 201):
Introduction to R/Python
for Data Science
Spring 2025
This course helped develop introductory skills in R and Python that I would need for data science.
Topics included:
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Data types (i.e integer, string, boolean)
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Data structures (i.e list, data frame)
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Control structures (i.e conditional statements)
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Good coding practices
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Reproducible coding
I become acquainted with basic data science algorithms and their implementations.
Final Project
Finding what features were a valuable website for an NC State Club
DSA 202:
Introduction to Data Visualization
Spring 2025
Visualizations can be one of the most effective means to communicate quantitative information.
I learned:
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Principles of effective visualization
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How to interpret data displays
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Different tools to display data visuals
One of my personal favorite
is Tableau!
Ulta Beauty Trends
A poster on the analysis of Ulta Beauty's '23
Fiscal Year report
(DSA 205):
Data Communication
Spring 2025
Knowing how to analyze your data is only half of the job:
you need to be able to present your research in a manner that your audience can understand.
Topics included:
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Learning to connect with your audience and meeting them where they are
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Offering tips for clear writing
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Creating accessible design of graphs and presentation slides
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A short and engaging reading of "If I Understood You, Would I Have This Look on My Face?" by Alan Alda
One of my favorite parts of this course was having improv lessons!
Class Work Examples
A communication written assignment and
a final presentation powerpoint