Welcome to The Data Chat readers!

I’m Anna and I’m currently a freshman at University of California, Davis majoring in Statistics and  pursuing a Data Science/Machine Learning track. One of the reasons I got attracted to Data Science is the interdisciplinary nature of the subject. In particular, I am interested in how data science is applied in the world of business.

My interest in business and data started while I was in high school. At Henry M Gunn High School in Palo Alto, I was involved with the business club DECA for all four years of high school. At Davis, I am involved in the Women in Business club as an External Relations Board Associate and am also very active in the data science club on the campus.

In addition, being in the heart of Silicon Valley, I also had the opportunity to do internships at startups that had AI-powered products as their core offerings. Couple of summers back, I interned at a startup in San Francisco backed by major VC firms like Insight Partners that provides an AI powered retail analytics product suite. I had the opportunity to learn a bit about how data science algorithms are used for sales forecasting.

This past summer, I interned with the data science team at EdCast, a market leader in the AI-powered Learning Experience Platform (LXP). EdCast is backed by major VC firms like Menlo Ventures and Softback and its core product is “spotify of learning” – a recommendation engine for corporate learners. I primarily worked on data analysis using the business intelligence tool DOMO and writing data processing scripts in Python. As part of my work, I ended up earning a certificate in Domo for data analysis.

During both of these internships, I had the good fortune to interact with some world class data scientists and data engineers and they were kind enough to provide me with guidance on how to prepare well for a career in data science with solid foundation on fundamentals.

This blog post series I hope to share my learnings with fellow students. In particular, I will write in the following areas to start with:

• Linear Algebra
• Statistical Learning
• Graph Theory
• Data Analysis & Processing
• Practical/Industry applications of Data Science

I also hope to bring in interviews with industry experts/academics who help us students prepare for a career/research in data science.

As for the story behind the name of this post, my high school geometry teacher told us a story about famous mathematician Euclid and Egyptian king Ptolemy I. Apparently, Ptolemy found Euclid’s seminal work “Elements” difficult to understand and asked if there was an easy road to master the concepts. Euclid is said to have said, “Sire, there’s no royal road to geometry” (Non est regia ad Geometriam).   

The road to data science mastery will entail learning many of the concepts through hard work and perseverance. Look forward to interacting with and learning from fellow travelers on the journey!