Academic Background
I earned my Bachelor’s degree in Economics from the University of California, Berkeley, where I developed a strong foundation in analytical thinking and quantitative methods. During my undergraduate years, I had the privilege of assisting several professors with their research projects, which sparked my passion for uncovering meaningful patterns within complex datasets.
Though the term “Data Science” hadn’t been coined yet, my research experiences at Berkeley laid the groundwork for what would become my career focus. Working alongside faculty members taught me the importance of rigorous methodology, critical thinking, and the art of translating complex findings into actionable insights.
Continuous Learning Journey
My educational journey didn’t end with my formal degree. Around the time I graduated, Massive Open Online Courses (MOOCs) were revolutionizing how people access quality education. I quickly embraced this new learning paradigm and enrolled in Coursera’s foundational Machine Learning course taught by Andrew Ng—a decision that would fundamentally shape my career trajectory.
Since then, I’ve maintained a commitment to lifelong learning, continuously updating my skills through online courses, technical books, and hands-on projects. This approach has allowed me to stay current with rapidly evolving technologies and methodologies in data science and machine learning.