The world of data science is like a vast and ever-expanding universe, and my journey into this realm began during a summer vacation when I decided to enroll in the UCLA data science online course. Little did I know that this choice would stimulate a profound passion and set me on a course of discovery and creation that continues to this day.

As I delved into the UCLA data science course, I found myself immersed in a world of numbers, algorithms, and analytical tools. What initially seemed like an academic pursuit quickly transformed into an exhilarating exploration. The course not only exposed me to the fundamental principles of data science but also empowered me to apply these principles in practical, real-world contexts.

My enthusiasm for data science found a natural home in my deep passion for baseball. To me, baseball is more than a sport; it's a treasure trove of rich analytical insights waiting to be unlocked. I recognized the immense potential that statistical data held in enhancing the experience of the game, both for dedicated fans and for the teams themselves. This realization led me to embark on a personal project that would not only satisfy my curiosity but also serve as a bridge between data science and baseball.

My project's objective is clear: to harness the extensive data on baseball statistics from the Korean Baseball Association spanning the past two decades. Armed with this wealth of information, I set out to develop machine learning algorithms capable of predicting a player's performance on a daily and annual basis. While Major League Baseball has begun to integrate user-friendly statistical prediction services, the Korean Baseball Organization (KBO) lags behind, offering fans only basic lists and tables that can be overwhelming even for seasoned enthusiasts.

To bridge this gap, my vision is to create an intuitive platform that not only presents these complex data points in an accessible manner but also predicts player performances. The goal is to transform intricate statistics into streamlined, user-centric prediction models that will not only benefit dedicated fans but also provide valuable insights for the teams and the league itself.

Throughout this journey, I've encountered numerous challenges and setbacks, but each obstacle has served as a valuable lesson. I've honed my skills in data science and data engineering, learning to refine my algorithms and improve the accuracy of predictions. The project has been a powerful teacher, not just in terms of technical skills, but also in the importance of perseverance and continuous learning.

My journey into data science and baseball analytics is an ongoing one, and I'm aware that there is much to learn and explore. Yet, I'm driven by the belief that this fusion of passions and skills has the potential to create meaningful change in the world of sports analytics and beyond. The excitement of discovering new insights and the thrill of transforming data into actionable knowledge fuel my dedication to this journey. With each step, I am becoming not just a data scientist but also a storyteller, uncovering the narratives hidden within the numbers and sharing them with the world.