Elizabeth Rychlinski, site creator

Data Science is an exciting field of study because there’s an endless list of technologies to learn, and there is plenty of open data on the web to explore while learning.

With so much to understand, becoming a Data Scientist can feel overwhelming. That’s why I’m documenting what I’m learning piece-by-piece on this blog. It’s a collection of projects, concepts, and tips related to Data Science.

My “data science stack” is evolving as I practice and study across various domains. To keep track of what I’ve done, and where I need to go, I’m tracking my progress:

I’ve separated my skills in mathematics and statistics and track those too:

What I’m learning

This is where I am currently focused:

• Time Series Analysis
• Bayesian Statistics

Programming-wise, I’m learning:

• Relational Databases and Data Modeling
• PostgreSQL
• Splunk
• R - Genarlized Linear Models, Surivival Analysis
• Python - Web Scraping, REST APIs, Natural Language Processing, ML