A blend of academic rigor and hands-on training—this is how a lifelong learner reverse-engineered a data science degree.
Credentials first. Story follows.
Credential Links
- Data Analytics Boot Camp, George Washington University
- Google Advanced Data Analytics Certificate
- Google Data Analytics Certificate
- cs50: Python
- cs50: SQL
- cs50: R
- cs50: Web Programming with Python and JavaScript
- cs50: Cybersecurity
- HarvardX: CS50's Introduction to Computer Science
Academic Degrees
- M.A. International Affairs, American University
- M.A. Natural Resources and Sustainable Development, United Nations University for Peace
Two Master’s degrees was enough tuition for a lifetime. When I pivoted to data analytics, I didn’t go back to school—I built my own. I started with a rigorous boot camp, then layered in top-tier MOOCs from Harvard, Google, and soon Stanford, stitching together the depth of a data science degree without the debt.
I don’t collect credentials; I pursue mastery. As a lifelong learner, I follow knowledge down the rabbit hole wherever it leads: past Python and SQL, through statistics and machine learning, and into the frontier of what’s next. I wanted the hard skills to complement my broad, interdisciplinary background. My goal was fluency, not familiarity.
These certifications reflect more than technical ability—they reflect intention, curiosity, and a commitment to depth over shortcuts.
Credentials
Academic Degrees
Side Quests
Easter Eggs. Conversation starters and whimsical extras.